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‎Files/DataTool.py‎

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# #################### Jadyn Wu ##################
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# Thank you for downloading Jadyn Wu's Program
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# I hope you find them useful in your projects
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# If you have any questions, find my contact in
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# my personal website below
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# Cheers!
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# JadynWu.com
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# --------------------------------------------------
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# Personal Website: https://jadynwu.com/
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# GitHub: https://github.com/YuudachiXMMY
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# ################################################
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import os, logging
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import numpy as np
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import pandas as pd
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import csv
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logging.basicConfig(filename="logs.log", filemode="w", level=logging.DEBUG)
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info = """
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#################### Jadyn Wu ##################
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Thank you for downloading Jadyn Wu's Program
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I hope you find them useful in your projects
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If you have any questions, find my contact in
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my personal website below
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Cheers!
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JadynWu.com
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--------------------------------------------------
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Personal Website: https://jadynwu.com/
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GitHub: https://github.com/YuudachiXMMY
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################################################
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"""
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print(info)
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logging.info(info)
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directory = os.path.abspath(os.path.join(os.path.curdir))
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print("Current Working Directory: " + directory)
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logging.info("Current Working Directory: " + directory)
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#check if dir exist if not create it
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def check_dir(file_name):
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directory = os.path.dirname(file_name)
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if not os.path.exists(directory):
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os.makedirs(directory)
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print(directory)
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def column_index(df, query_cols):
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cols = df.columns.values
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sidx = np.argsort(cols)
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return sidx[np.searchsorted(cols,query_cols,sorter=sidx)]
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def transformToGameData():
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output_file = directory+'//vehicleGroupData.csv'
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check_dir(output_file)
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with open(output_file, 'w', newline='') as file:
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writer = csv.writer(file)
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writer.writerow(["SN", "Movie", "Protagonist"])
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car_color_dict = {
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"green" : 0,
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"orange" : 0,
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"black" : 1,
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"red" : 2,
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"blue" : 3,
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"white" : 4
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}
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def addFunctionToData(row):
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res = ''
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if row["facial_tag"]:
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res += 'facerecog/'
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if row["glasses_tag"]:
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res += 'glasses/'
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if row["language_tag"]:
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res += 'language/'
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if row["pwd_tag"]:
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res += 'password/'
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if row["distance_tag"]:
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res += 'distance/'
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if row["male_tag"]:
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res += 'male/'
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return res.strip("/")
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def parseData(file_name="input.xlsx"):
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input_df = pd.read_excel(file_name)
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input_df["name_length"] = input_df.iloc[:,6].apply(lambda x: len(x))
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# Cleaning for Data Analysis
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input_df["avg_facial"] = input_df.iloc[:,10].mean()
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input_df["avg_glasses"] = input_df.iloc[:,11].mean()
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input_df["avg_language"] = input_df.iloc[:,12].mean()
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input_df["avg_pwd"] = input_df.iloc[:,14].mean()
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input_df["avg_distance"] = input_df.iloc[:,15].mean()
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input_df["avg_nameLength"] = input_df["name_length"].mean()
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# Analysis DF
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avg_df = input_df[["avg_nameLength", "avg_facial", "avg_glasses", "avg_language", "avg_pwd", "avg_distance"]]
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avg_df = avg_df.round(0)
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# Cleaning for Game df
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input_df["facial_tag"] = input_df["avg_facial"] <= input_df.iloc[:,10]
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input_df["glasses_tag"] = input_df["avg_glasses"] <= input_df.iloc[:,11]
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input_df["language_tag"] = input_df["avg_language"] <= input_df.iloc[:,12]
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input_df["pwd_tag"] = input_df["avg_pwd"] >= input_df.iloc[:,14]
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input_df["distance_tag"] = input_df["avg_distance"] <= input_df.iloc[:,15]
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input_df["male_tag"] = input_df.iloc[:,13].apply(lambda x: True if x>2 else False)
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input_df['functions'] = input_df.apply(addFunctionToData, axis=1)
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# Game df
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df = input_df.iloc[:, [6,7, column_index(input_df, ['functions'])[0]]]
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df.columns = ['name', 'vehicle', 'functions']
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df.iloc[:,1] = df.iloc[:,1].apply(lambda x: car_color_dict[x.lower()])
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return df, avg_df
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try:
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print("Parsing the input.xlsx file...")
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logging.info("Parsing the input.xlsx file...")
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df, avg_df = parseData()
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print("Success!")
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logging.info("Success!")
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except Exception as e:
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logging.error('Error at %s', 'division', exc_info=e)
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try:
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print("Saving vehicleGroupData.csv file...")
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logging.info("Saving vehicleGroupData.csv file...")
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df.to_csv('vehicleGroupData.csv', sep=',', encoding='utf-8', index=False, header=False)
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print("Success!")
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logging.info("Success!")
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except Exception as e:
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logging.error('Error at %s', 'division', exc_info=e)
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try:
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print("Saving AvgAnalysis.csv file...")
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logging.info("Saving AvgAnalysis.csv file...")
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avg_df.iloc[0:1,:].to_csv('AvgAnalysis.csv', sep=',', encoding='utf-8', index=False, header=True)
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print("Success!")
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logging.info("Success!")
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except Exception as e:
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logging.error('Error at %s', 'division', exc_info=e)
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# #################### Jadyn Wu ##################
2+
# Thank you for downloading Jadyn Wu's Program
3+
# I hope you find them useful in your projects
4+
# If you have any questions, find my contact in
5+
# my personal website below
6+
# Cheers!
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# JadynWu.com
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# --------------------------------------------------
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# Personal Website: https://jadynwu.com/
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# GitHub: https://github.com/YuudachiXMMY
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# ################################################
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import os, logging
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import numpy as np
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import pandas as pd
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import csv
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logging.basicConfig(filename="logs.log", filemode="w", level=logging.DEBUG)
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info = """
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#################### Jadyn Wu ##################
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Thank you for downloading Jadyn Wu's Program
22+
I hope you find them useful in your projects
23+
If you have any questions, find my contact in
24+
my personal website below
25+
Cheers!
26+
JadynWu.com
27+
--------------------------------------------------
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Personal Website: https://jadynwu.com/
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GitHub: https://github.com/YuudachiXMMY
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################################################
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"""
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print(info)
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logging.info(info)
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directory = os.path.abspath(os.path.join(os.path.curdir))
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print("Current Working Directory: " + directory)
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logging.info("Current Working Directory: " + directory)
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#check if dir exist if not create it
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def check_dir(file_name):
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directory = os.path.dirname(file_name)
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if not os.path.exists(directory):
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os.makedirs(directory)
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print(directory)
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def column_index(df, query_cols):
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cols = df.columns.values
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sidx = np.argsort(cols)
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return sidx[np.searchsorted(cols,query_cols,sorter=sidx)]
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def transformToGameData():
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output_file = directory+'//vehicleGroupData.csv'
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check_dir(output_file)
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with open(output_file, 'w', newline='') as file:
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writer = csv.writer(file)
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writer.writerow(["SN", "Movie", "Protagonist"])
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car_color_dict = {
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"green" : 0,
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"orange" : 0,
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"black" : 1,
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"red" : 2,
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"blue" : 3,
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"white" : 4
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}
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def addFunctionToData(row):
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res = ''
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if row["facial_tag"]:
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res += 'facerecog/'
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if row["glasses_tag"]:
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res += 'glasses/'
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if row["language_tag"]:
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res += 'language/'
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if row["pwd_tag"]:
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res += 'password/'
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if row["distance_tag"]:
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res += 'distance/'
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if row["male_tag"]:
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res += 'male/'
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return res.strip("/")
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def parseData(file_name="input.csv"):
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try:
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print("Trying to Read file: " + file_name)
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if file_name.endswith('.csv'):
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input_df = pd.read_csv(file_name)
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else:
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input_df = pd.read_excel(file_name)
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print("Success!")
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logging.info("Success!")
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except:
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print("Cannot Read file: " + file_name)
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logging.info("Cannot Read file: " + file_name)
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try:
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print("Try reading input.csv")
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logging.info("Try reading input.csv")
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input_df = pd.read_csv("input.csv")
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print("Success!")
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logging.info("Success!")
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except Exception as e:
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logging.error('Error at %s', 'division', exc_info=e)
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print("Parsing the file...")
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logging.info("Parsing the file...")
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input_df["name_length"] = input_df.iloc[:,6].apply(lambda x: len(x))
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# Cleaning for Data Analysis
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input_df["avg_facial"] = input_df.iloc[:,10].mean()
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input_df["avg_glasses"] = input_df.iloc[:,11].mean()
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input_df["avg_language"] = input_df.iloc[:,12].mean()
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input_df["avg_pwd"] = input_df.iloc[:,14].mean()
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input_df["avg_distance"] = input_df.iloc[:,15].mean()
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input_df["avg_nameLength"] = input_df["name_length"].mean()
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# Analysis DF
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avg_df = input_df[["avg_nameLength", "avg_facial", "avg_glasses", "avg_language", "avg_pwd", "avg_distance"]]
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avg_df = avg_df.round(0)
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# Cleaning for Game df
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input_df["facial_tag"] = input_df["avg_facial"] <= input_df.iloc[:,10]
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input_df["glasses_tag"] = input_df["avg_glasses"] <= input_df.iloc[:,11]
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input_df["language_tag"] = input_df["avg_language"] <= input_df.iloc[:,12]
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input_df["pwd_tag"] = input_df["avg_pwd"] >= input_df.iloc[:,14]
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input_df["distance_tag"] = input_df["avg_distance"] <= input_df.iloc[:,15]
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input_df["male_tag"] = input_df.iloc[:,13].apply(lambda x: True if x>2 else False)
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input_df['functions'] = input_df.apply(addFunctionToData, axis=1)
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# Game df
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df = input_df.iloc[:, [6,7, column_index(input_df, ['functions'])[0]]]
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df.columns = ['name', 'vehicle', 'functions']
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df.iloc[:,1] = df.iloc[:,1].apply(lambda x: car_color_dict[x.lower()])
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return df, avg_df
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def readInput():
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res = input("""
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Please enter your file name
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press enter directly to read input.csv
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(e.g. input.csv , Class1.xlsx)
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""")
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if res == "":
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res = "input.csv"
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return res
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try:
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res = readInput()
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df, avg_df = parseData(res)
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print("Success!")
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logging.info("Success!")
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try:
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print("Saving vehicleGroupData.csv file...")
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logging.info("Saving vehicleGroupData.csv file...")
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df.to_csv('vehicleGroupData.csv', sep=',', encoding='utf-8', index=False, header=False)
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print("Success!")
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logging.info("Success!")
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except Exception as e:
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logging.error('Error at %s', 'division', exc_info=e)
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try:
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print("Saving AvgAnalysis.csv file...")
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logging.info("Saving AvgAnalysis.csv file...")
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avg_df.iloc[0:1,:].to_csv('AvgAnalysis.csv', sep=',', encoding='utf-8', index=False, header=True)
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print("Success!")
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logging.info("Success!")
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except Exception as e:
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logging.error('Error at %s', 'division', exc_info=e)
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except Exception as e:
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logging.error('Error at %s', 'division', exc_info=e)

Files/dist/DataTool.exe renamed to Files/dist/DataTool-v0.exe

File renamed without changes.

‎Files/dist/DataTool-v1.exe‎

87.7 MB
Binary file not shown.

‎Files/dist/READ_ME.txt‎

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#################### Jadyn Wu ##################
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Thank you for downloading Jadyn Wu's Program
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I hope you find them useful in your projects
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If you have any questions, find my contact in
5+
my personal website below
6+
Cheers!
7+
JadynWu.com
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--------------------------------------------------
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Personal Website: https://jadynwu.com/
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GitHub: https://github.com/YuudachiXMMY
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################################################
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################# Program Specification ##############
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Input file:
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- input.csv
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output files:
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- vehicleGroupData.csv : used for game program
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- AvgAnalysis.csv : analysis the average information of some data
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Before RUNNING, please ensrue that:
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1. The input file is renamed to input.csv
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2. DataTool.exe and input.csv are in the SAME folder/directory
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To RUN:
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1. Double-Click the DataTool.exe
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Data format of input.csv:
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- Names must be in column G
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- Colors must be in column H
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- Number of Team Members must be in column I
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- Facial Recognition must be in column K
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- Glassess must be in column L
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- Languages must be in column M
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- Number of People identifying themselve as Male must be in column N
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- Password must be in column O
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- Distance must be in column P

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