forked from Open-CT/opendata
839 lines
51 KiB
Python
839 lines
51 KiB
Python
import pandas as pd
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import json
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import numpy as np
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import ast
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from datetime import datetime
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import plotly.graph_objs as go
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from plotly.offline import plot
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import plotly.offline as offline
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from pandas.core.indexes import interval
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import re
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from pathlib import Path
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import os
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class data_analysis:
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def __init__(self, df, name = 'default') -> None:
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self.accuracy_list, self.addition_list =0, 0
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self.name = name
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self.with_successrate = [0, 1]
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self.df = df
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self.problem_num = len(ast.literal_eval(self.df.loc[0, 'task_answers']))
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self.row_num = len(self.df)
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self.df.insert(len(self.df.columns), 'ans', self.remove_str())
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self.df.insert(len(self.df.columns), 'interval', self.get_interval()[0])
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self.df.insert(len(self.df.columns), 'day', self.get_interval()[1])
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self.df.insert(len(self.df.columns), 'start_hour', self.get_interval()[2])
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self.df.insert(len(self.df.columns), 'end_hour', self.get_interval()[3])
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self.df.insert(len(self.df.columns), 'start_time_float', self.get_interval()[4])
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if -1 in self.df.sort_values(by='start_hour', ascending=True).groupby('start_hour').groups.keys():
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self.df = self.df.drop(list(self.df.sort_values(by='start_hour', ascending=True).groupby('start_hour').groups[-1]))
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self.df = self.df.reset_index(drop=True)
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self.row_num = len(self.df)
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self.ndf = pd.DataFrame(self.create_new_df())
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self.ndf_list = self.divide_ndf()
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self.group_list = self.group_by()
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self.count_df_list = self.count_group()
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# self.addition_list, self.success_df,self.problem_num_list = self.get_addition()
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# self.output_df = 0
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# self.output()
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print('init complete')
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def remove_time_error(self):
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df_rm_time_err = 0
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return df_rm_time_err
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def remove_str_per_row(self, data_per_row):
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frame_list = ast.literal_eval(data_per_row)
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frame_dic_list = []
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for index in range(len(frame_list)):
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if frame_list[index] == '':
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frame_dic_list.append({'frame':'0'})
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else:
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frame_dic_list.append(json.loads(frame_list[index]))
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return frame_dic_list
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def remove_str(self):
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ndf_ans_8_list = []
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ndf_rm_frame = []
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for i in range(self.row_num):
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dic_temp = self.remove_str_per_row(self.df.loc[i,'task_answers'])
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ndf_ans_8_list.append(dic_temp)
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new_dic_list = []
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for dic in dic_temp:
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dic = dic['frame']
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new_dic = dic
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new_dic_list.append(new_dic)
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ndf_rm_frame.append(new_dic_list)
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return ndf_rm_frame
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def get_interval(self):
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interval_list = []
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day_list = []
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start_hour_list = []
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stop_hour_list = []
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start_time_list = []
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for i in range(len(self.df)):
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interval_list.append(self.get_interval_per_row(i)[0])
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day_list.append(self.get_interval_per_row(i)[1])
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start_hour_list.append(self.get_interval_per_row(i)[2])
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stop_hour_list.append(self.get_interval_per_row(i)[3])
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start_time_list.append(self.get_interval_per_row(i)[4])
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return [interval_list, day_list, start_hour_list, stop_hour_list, start_time_list]
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def get_interval_per_row(self, index):
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row_data = self.df.loc[index,:]
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start_time = row_data['start_time']
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if start_time != start_time:
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return -1, -1, -1, -1, -1
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start_time = datetime.strptime(start_time,"%Y-%m-%dT%H:%M:%S+08:00")
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expire_time = row_data['expire_time']
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expire_time = datetime.strptime(expire_time,"%Y-%m-%dT%H:%M:%S+08:00")
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stop_time = row_data['stop_time']
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if stop_time != stop_time:
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return -1, -1, -1, -1, -1
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stop_time = datetime.strptime(stop_time,"%Y-%m-%dT%H:%M:%S+08:00")
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total_sec = (stop_time - start_time).seconds
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return [total_sec, str(start_time.month)+str(start_time.day), start_time.hour, stop_time.hour, start_time.hour+start_time.minute/60.0]
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def create_new_df(self):
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twoD_list = []
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for row in range(self.row_num):
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ans_dic_list = self.df.loc[row, 'ans']
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twoD_list.append(ans_dic_list)
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return twoD_list
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def divide_ndf(self):
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ndf_list = []
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for i in range(len(self.ndf.columns)):
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ndf_list.append(pd.DataFrame(self.ndf.loc[:,i]))
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return ndf_list
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def group_by_per_problem(self, index):
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df_temp = self.ndf_list[index]
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df_str_list = []
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for j in range(len(df_temp)):
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ndf_index_j = df_temp.iloc[j, 0]
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if ndf_index_j == None:
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df_str_list.append(str(None))
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else:
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df_str_list.append(self.content_to_str(ndf_index_j))
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df_temp.insert(1, 'ans_str', df_str_list)
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df_per_problom = df_temp.groupby('ans_str')
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return df_per_problom
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def content_to_str(self, data):
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if data == None or type(data) == str:
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return str(None)
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elif type(data) == type([]):
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return self.data_to_str(data)
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elif 'data' in data.keys():
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return self.data_to_str(data['data'])
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else:
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return self.data_to_str(data)
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def data_to_str(self, data):
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if type(data) == type({}):
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return str(list(data.values()))
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else:
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return str(data)
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def main_df_process(self):
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return 0
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def group_by(self):
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group_list = []
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for i in range(self.problem_num):
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df_temp = self.group_by_per_problem(i)
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group_list.append(df_temp)
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return group_list
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def count_group(self):
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count_df_list = []
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for group in self.group_list:
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count_df_list.append(group.count())
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return count_df_list
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def plot(self):
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data = [go.Histogram(x=list(self.df.loc[:,'interval']))]
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layout={"title": "学生用时分布",
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"xaxis_title": "学生用时，单位秒",
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"yaxis_title": "学生个数",
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# x轴坐标倾斜60度
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"xaxis": {"tickangle": 60}
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}
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fig = go.Figure(data=data,layout=layout)
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plot(fig,filename="./plot/"+self.name+"/time.html",auto_open=False,image='png',image_height=800,image_width=1500)
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# offline.iplot(fig)
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return 0
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def plot_problem(self):
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data = [go.Bar(x = list(range(self.problem_num)), y = [len(list(group)) for group in self.group_list])]
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layout={"title": "不同题目的编码数量",
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"xaxis_title": "题目编号",
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"yaxis_title": "编码个数",
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# x轴坐标倾斜60度
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"xaxis": {"tickangle": 60}
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}
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fig = go.Figure(data=data,layout=layout)
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plot(fig,filename="./plot/"+self.name+"/plot_problem.html",auto_open=False,image='png',image_height=800,image_width=1500)
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# offline.iplot(fig)
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return 0
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def output(self):
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tar_path = './output/added_columns/'+self.name
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if not os.path.exists(tar_path):
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os.makedirs(tar_path)
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self.df.to_excel(tar_path+'/' +'data_added_columns.xlsx')
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def calculate_acc(self):
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accuracy_list = []
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addition_list = []
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for i, df in enumerate(self.count_df_list):
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print(i)
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additional_infor_df = pd.DataFrame({'list':[ast.literal_eval(index) for index in df.index]})
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additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( df.iloc[:, 0]))
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# additional_infor_df.to_excel('./output/all'+'/' +str(i) + '_count.xlsx')
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if i in [0, 1]:
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drop_index_list = []
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for j in range(len(additional_infor_df)):
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if additional_infor_df.iloc[j,0]== None:
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drop_index_list.append(j)
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elif len(additional_infor_df.iloc[j,0]) != 4:
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drop_index_list.append(j)
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additional_infor_df = additional_infor_df.drop(drop_index_list)
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additional_infor_df = additional_infor_df.reset_index(drop=True)
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additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( additional_infor_df.loc[:, 'count'])])
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additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['0' if l==None else str(l[0]) for l in additional_infor_df.iloc[:,0] ])
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if len(list(additional_infor_df.groupby('success'))) == 2:
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if list(additional_infor_df.groupby('success'))[1][0] == '1':
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
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else:
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
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elif len(list(additional_infor_df.groupby('success'))) == 1:
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if list(additional_infor_df.groupby('success'))[0][0] == '1':
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accuracy_list.append(1.0)
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else:
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accuracy_list.append(0.0)
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else:
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accuracy_list.append(0.0)
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elif i in [2,3]:
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drop_index_list = []
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for j in range(len(additional_infor_df)):
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if additional_infor_df.iloc[j,0]== None:
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drop_index_list.append(j)
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elif len(additional_infor_df.iloc[j,0]) == 0:
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drop_index_list.append(j)
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elif type(additional_infor_df.iloc[j,0][0]) != str:
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drop_index_list.append(j)
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additional_infor_df = additional_infor_df.drop(drop_index_list)
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additional_infor_df = additional_infor_df.reset_index(drop=True)
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additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( additional_infor_df.loc[:, 'count'])])
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additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l!= None and len(l)!=0 and l[0]=='00' else '0' for l in additional_infor_df.iloc[:,0] ])
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if len(list(additional_infor_df.groupby('success'))) == 2:
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if list(additional_infor_df.groupby('success'))[1][0] == '1':
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
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else:
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
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elif len(list(additional_infor_df.groupby('success'))) == 1:
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if list(additional_infor_df.groupby('success'))[0][0] == '1':
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accuracy_list.append(1.0)
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else:
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accuracy_list.append(0.0)
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else:
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accuracy_list.append(0.0)
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elif i in [5]:
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drop_index_list = []
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for j in range(len(additional_infor_df)):
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if additional_infor_df.iloc[j,0]== None:
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drop_index_list.append(j)
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elif len(additional_infor_df.iloc[j,0]) == 0:
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drop_index_list.append(j)
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elif type(additional_infor_df.iloc[j,0][0]) != str:
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drop_index_list.append(j)
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additional_infor_df = additional_infor_df.drop(drop_index_list)
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additional_infor_df = additional_infor_df.reset_index(drop=True)
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additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( additional_infor_df.loc[:, 'count'])])
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additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l!= None and len(l)==2 and l[0]+l[1]=='B_AC_A' else '0' for l in additional_infor_df.iloc[:,0] ])
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if len(list(additional_infor_df.groupby('success'))) == 2:
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if list(additional_infor_df.groupby('success'))[1][0] == '1':
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
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else:
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
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elif len(list(additional_infor_df.groupby('success'))) == 1:
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if list(additional_infor_df.groupby('success'))[0][0] == '1':
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accuracy_list.append(1.0)
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else:
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accuracy_list.append(0.0)
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else:
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accuracy_list.append(0.0)
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elif i in [6]:
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drop_index_list = []
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for j in range(len(additional_infor_df)):
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if additional_infor_df.iloc[j,0]== None:
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drop_index_list.append(j)
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elif len(additional_infor_df.iloc[j,0]) == 0:
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drop_index_list.append(j)
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elif type(additional_infor_df.iloc[j,0][0]) != str:
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drop_index_list.append(j)
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additional_infor_df = additional_infor_df.drop(drop_index_list)
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additional_infor_df = additional_infor_df.reset_index(drop=True)
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additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( additional_infor_df.loc[:, 'count'])])
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additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l!= None and len(l)==5 and l[0]+l[1]+l[2]+l[3]+l[4]=='B_AC_AG_FD_BE_B' else '0' for l in additional_infor_df.iloc[:,0] ])
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if len(list(additional_infor_df.groupby('success'))) == 2:
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if list(additional_infor_df.groupby('success'))[1][0] == '1':
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
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else:
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
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elif len(list(additional_infor_df.groupby('success'))) == 1:
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if list(additional_infor_df.groupby('success'))[0][0] == '1':
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accuracy_list.append(1.0)
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else:
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accuracy_list.append(0.0)
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else:
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accuracy_list.append(0.0)
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elif i in [7]:
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drop_index_list = []
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for j in range(len(additional_infor_df)):
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if additional_infor_df.iloc[j,0]== None:
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drop_index_list.append(j)
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elif len(additional_infor_df.iloc[j,0]) != 4:
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drop_index_list.append(j)
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elif type(additional_infor_df.iloc[j,0][0]) != list or type(additional_infor_df.iloc[j,0][1]) != list or type(additional_infor_df.iloc[j,0][2]) != list or type(additional_infor_df.iloc[j,0][3]) != list:
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drop_index_list.append(j)
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additional_infor_df = additional_infor_df.drop(drop_index_list)
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additional_infor_df = additional_infor_df.reset_index(drop=True)
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additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( additional_infor_df.loc[:, 'count'])])
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additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l!= None and len(l)==4 and [[0,1],[0,2],[1,2]] in l and [[0,4],[0,5],[1,5]] in l and [[0,6],[0,7],[1,7]] in l and [[0,10],[0,11],[1,11]] else '0' for l in additional_infor_df.iloc[:,0] ])
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if len(list(additional_infor_df.groupby('success'))) == 2:
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if list(additional_infor_df.groupby('success'))[1][0] == '1':
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
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else:
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
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elif len(list(additional_infor_df.groupby('success'))) == 1:
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if list(additional_infor_df.groupby('success'))[0][0] == '1':
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accuracy_list.append(1.0)
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else:
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accuracy_list.append(0.0)
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else:
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accuracy_list.append(0.0)
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elif i in [8] :
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drop_index_list = []
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for j in range(len(additional_infor_df)):
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if additional_infor_df.iloc[j,0]== None:
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drop_index_list.append(j)
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elif len(additional_infor_df.iloc[j,0]) != 5:
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drop_index_list.append(j)
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elif type(additional_infor_df.iloc[j,0][0]) != list or type(additional_infor_df.iloc[j,0][1]) != list or type(additional_infor_df.iloc[j,0][2]) != list or type(additional_infor_df.iloc[j,0][3]) != list or type(additional_infor_df.iloc[j,0][4]) != list:
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drop_index_list.append(j)
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additional_infor_df = additional_infor_df.drop(drop_index_list)
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additional_infor_df = additional_infor_df.reset_index(drop=True)
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additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( additional_infor_df.loc[:, 'count'])])
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verify_list = [[[1, 0], [2, 0], [3, 0], [3, 1]], [[0, 1], [1, 1], [2, 1], [2, 2]], [[3, 2], [4, 2], [5, 2], [5, 3]], [[2, 3], [3, 3], [4, 3], [4, 4]], [[0, 4], [1, 4], [2, 4], [2, 5]]]
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additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l!= None and len(l)==5 and verify_list[0] in l and verify_list[1] in l and verify_list[2] in l and verify_list[3] in l and verify_list[4] in l else '0' for l in additional_infor_df.iloc[:,0] ])
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if len(list(additional_infor_df.groupby('success'))) == 2:
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if list(additional_infor_df.groupby('success'))[1][0] == '1':
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accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [9]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0]) == 0:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0][0]) != str:
|
|
drop_index_list.append(j)
|
|
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row,'list']
|
|
if list_temp!=None and len(list_temp)==2:
|
|
if list_temp[0][0:2] > list_temp[0][-2:]:
|
|
list_temp[0] = list_temp[0][-2:] + '_' + list_temp[0][0:2]
|
|
if list_temp[1][0:2] > list_temp[1][-2:]:
|
|
list_temp[1] = list_temp[1][-2:] + '_' + list_temp[1][0:2]
|
|
if list_temp[0] > list_temp[1]:
|
|
additional_infor_df._set_value(row,'list', str([list_temp[1], list_temp[0]]))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', str(list_temp))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', str(list_temp))
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[ast.literal_eval(index) for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
verify_list = [['02_09', '05_06'],['02_05', '06_09'],['02_06', '05_09']]
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l!= None and len(l)==2 and l in verify_list else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [10]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0]) == 0:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0][0]) != str:
|
|
drop_index_list.append(j)
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
|
|
if list_temp!=None:
|
|
list_temp = [[int(rebuild_i) for rebuild_i in re.findall(r"\d+", rebuild)] for rebuild in list_temp]
|
|
for list_mem in list_temp:
|
|
list_mem.sort()
|
|
list_temp.sort()
|
|
additional_infor_df._set_value(row,'list', str([str(list_str[0]) + '_' + str(list_str[1]) for list_str in list_temp]))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', str(list_temp))
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[ast.literal_eval(index) for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
verify_list = ['2','6','12','14','15','16']
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l!= None and len(l)==3 and len(set([re.findall(r"\d+",l[0])[0], re.findall(r"\d+",l[0])[1], re.findall(r"\d+",l[1])[0], re.findall(r"\d+",l[1])[1], re.findall(r"\d+",l[2])[0],re.findall(r"\d+",l[2])[1]]))==6 and re.findall(r"\d+",l[0])[0] in verify_list and re.findall(r"\d+",l[0])[1] in verify_list and re.findall(r"\d+",l[1])[0] in verify_list and re.findall(r"\d+",l[1])[1] in verify_list and re.findall(r"\d+",l[2])[0] in verify_list and re.findall(r"\d+",l[2])[1] in verify_list else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [11]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0]) == 0:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0]) == 0:
|
|
drop_index_list.append(j)
|
|
elif None in additional_infor_df.iloc[j,0][0]:
|
|
drop_index_list.append(j)
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', "".join(re.findall(r"\d+", str(list_temp))))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
verify_str = '0012210224'
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l==verify_str else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [12]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0]) == 0:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0]) == 0:
|
|
drop_index_list.append(j)
|
|
elif None in additional_infor_df.iloc[j,0][0]:
|
|
drop_index_list.append(j)
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', "".join(re.findall(r"\d+", str(list_temp))))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
verify_str = '2213110425'
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l==verify_str else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [13]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0]) != 2:
|
|
drop_index_list.append(j)
|
|
else:
|
|
for n in additional_infor_df.iloc[j,0]:
|
|
if type(n) != int:
|
|
drop_index_list.append(j)
|
|
break
|
|
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', "".join(re.findall(r"\d+", str(list_temp))))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
verify_str = '21'
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l==verify_str else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [14]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0]) != 6:
|
|
drop_index_list.append(j)
|
|
else:
|
|
for n in additional_infor_df.iloc[j,0]:
|
|
if type(n) != int:
|
|
drop_index_list.append(j)
|
|
break
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', "".join(re.findall(r"\d+", str(list_temp))))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
verify_str = '121223'
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l==verify_str else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [15]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0])==0 or type(additional_infor_df.iloc[j,0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0])==0 or type(additional_infor_df.iloc[j,0][0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0][0])!=3:
|
|
drop_index_list.append(j)
|
|
else:
|
|
for n in additional_infor_df.iloc[j,0][0][0]:
|
|
if type(n) != int:
|
|
drop_index_list.append(j)
|
|
break
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', "".join(re.findall(r"\d+", str(list_temp))))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
|
|
verify_list = ['0', '2']
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if len(l)==3 and l[0] in verify_list and l[1] in verify_list and l[2] in verify_list else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [16]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0])==0 or type(additional_infor_df.iloc[j,0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0])==0 or type(additional_infor_df.iloc[j,0][0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0][0])!=6:
|
|
drop_index_list.append(j)
|
|
else:
|
|
for n in additional_infor_df.iloc[j,0][0][0]:
|
|
if type(n) != int:
|
|
drop_index_list.append(j)
|
|
break
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', "".join(re.findall(r"\d+", str(list_temp))))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
|
|
verify_str = '000000'
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l.replace('2','0')==verify_str else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [17]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0])==0 or type(additional_infor_df.iloc[j,0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0])!=7:
|
|
drop_index_list.append(j)
|
|
else:
|
|
for n in additional_infor_df.iloc[j,0][0]:
|
|
if n not in [0, 1]:
|
|
drop_index_list.append(j)
|
|
break
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', "".join(re.findall(r"\d+", str(list_temp))))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
verify_str = '1010011001'
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l==verify_str else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [18]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0])==0 or type(additional_infor_df.iloc[j,0][0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0][0])<1:
|
|
drop_index_list.append(j)
|
|
else:
|
|
for n in additional_infor_df.iloc[j,0][0]:
|
|
if n not in [0, 1]:
|
|
drop_index_list.append(j)
|
|
break
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', str(list_temp))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
|
|
verify_list = ['[[0, 0, 1, 1, 0, 1, 0], [[1, 0], [0]]]','[[1, 1, 0, 0, 1, 0, 1], [[0], [1, 0]]]']
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l in verify_list else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
elif i in [19]:
|
|
drop_index_list = []
|
|
for j in range(len(additional_infor_df)):
|
|
if additional_infor_df.iloc[j,0]== None:
|
|
drop_index_list.append(j)
|
|
elif type(additional_infor_df.iloc[j,0]) != list:
|
|
drop_index_list.append(j)
|
|
elif len(additional_infor_df.iloc[j,0])!=4 or type(additional_infor_df.iloc[j,0][0]) != list or type(additional_infor_df.iloc[j,0][1]) != int or type(additional_infor_df.iloc[j,0][2]) != int:
|
|
drop_index_list.append(j)
|
|
else:
|
|
for n in additional_infor_df.iloc[j,0][0]:
|
|
if n not in [0, 1, 2]:
|
|
drop_index_list.append(j)
|
|
break
|
|
additional_infor_df = additional_infor_df.drop(drop_index_list)
|
|
additional_infor_df = additional_infor_df.reset_index(drop=True)
|
|
|
|
for row in range(len(additional_infor_df)):
|
|
list_temp = additional_infor_df.loc[row, 'list']
|
|
if list_temp!=None:
|
|
additional_infor_df._set_value(row,'list', str(list_temp))
|
|
else:
|
|
additional_infor_df._set_value(row,'list', '')
|
|
grouped = additional_infor_df.groupby('list')['count'].sum()
|
|
additional_infor_df = pd.DataFrame({'list':[index for index in grouped.index]})
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'count', list( grouped.iloc[:]))
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'ratio', [int(l)*100/float(self.row_num) for l in list( grouped.iloc[:])])
|
|
verify_str = '[[1, 0, 1, 2], 1, 16, True]'
|
|
additional_infor_df.insert(len(additional_infor_df.columns), 'success', ['1' if l==verify_str else '0' for l in additional_infor_df.iloc[:,0] ])
|
|
if len(list(additional_infor_df.groupby('success'))) == 2:
|
|
if list(additional_infor_df.groupby('success'))[1][0] == '1':
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[1]/self.row_num)
|
|
else:
|
|
accuracy_list.append(additional_infor_df.groupby('success')['count'].sum().iloc[0]/self.row_num)
|
|
elif len(list(additional_infor_df.groupby('success'))) == 1:
|
|
if list(additional_infor_df.groupby('success'))[0][0] == '1':
|
|
accuracy_list.append(1.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
else:
|
|
accuracy_list.append(0.0)
|
|
if i not in [4, 20,21]:
|
|
addition_list.append(additional_infor_df)
|
|
tar_path = './output/acc/'+self.name+'_acc'
|
|
if not os.path.exists(tar_path):
|
|
os.makedirs(tar_path)
|
|
additional_infor_df.to_excel(tar_path+'/' +str(i) + '_acc.xlsx')
|
|
self.accuracy_list, self.addition_list = accuracy_list, addition_list
|
|
return accuracy_list, addition_list
|
|
|
|
if __name__ == '__main__':
|
|
df = pd.read_excel('./data/ticket_user_mianyang.xlsx')
|
|
# df_junior = pd.read_excel('./data/junior.xlsx')
|
|
# df_senior = pd.read_excel('./data/senior.xlsx')
|
|
data_entity = data_analysis(df)
|
|
# data_entity_junior = data_analysis(df = df_junior, name = 'junior')
|
|
# data_entity_senior = data_analysis(df = df_senior, name = 'senior')
|