LabApplicationProgramming/main.py at main · pafosz/LabApplicationProgramming · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
from modules import loading_links
from modules import parser_data as prd
from modules import add_functions as af
from modules import division_data as dd
from modules import data_iterator as di
from modules import correction_dataset as cd
from modules import plot_graph as pg
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt


# # !autopep8 --in-place --aggressive --aggressive uglycodesample.py

#def main():
#     # loading_links.writes_list_file('datasets/url_list.txt', 1993)
#     # parser_data.upload_csv('datasets/url_list.txt', 'datasets/dataset.csv')
#     #af.replace_date_format('datasets/dataset.csv')
#     # dd.division_date_and_data('datasets', 'date_and_data', 'dataset.csv')
#     # dd.division_by_year('datasets', 'data_by_year', 'dataset.csv')
#     # dd.division_by_week('datasets', 'data_by_week', 'dataset.csv')


#     it = di.DataIterator()
#     print(next(it))
path = "dataset1.csv"
df = pd.read_csv(path)

df['data'] = df['data'].str.replace('-', 'NaN')

df['data'] = df['data'].astype(float)
df.dropna(inplace=True)
df.reset_index(drop=True, inplace=True)

print(df)

df.to_csv(path, index=False)


# df = pd.DataFrame(df)
# df['date'] = pd.to_datetime(df['date'])

# mm = cd.group_by_month(df)

# print(mm)


# if __name__ == "__main__":
#    main()