Максим Припадчев

metrics_df[[
    "same_intervals_between_requests"

df[["time_local", "id_session"]].groupby("id_session").apply(count_metric_using_shift)

df = pd.DataFrame({
    'Cat':['A','A','B','A','B'],
    'Num1':[1,2,3,4,5],
    'Num2':[6,7,8,9,10]
})
df[['A','B']] = df[['Cat']].groupby('Cat').apply('mean')

df= pd.DataFrame({'time':pd.date_range('2023-03-22', periods=48, freq='H')})
bins = [0,5,11,16,22,24]
labels = ['Ночь', 'Утро','День','Вечер','Ночь']
df['session'] = pd.cut(df['time'].dt.hour, bins=bins, labels=labels, include_lowest=True,ordered=False)
df

from itertools import zip_longest
print(list(zip(*zip_longest(*testList, fillvalue=None))))

df[df.name.str.contains('i3|oem', regex=True, case=False)])

df = pd.DataFrame({
    'name':['23i3f','dOemf','25','s2f5','df5'],
    'amount':[1,2,3,4,5]
})

print(df[df.name.str.contains('i3|oem',regex=True,flags=re.IGNORECASE)])

W1 = np.random.randn(IND, HD)
b1 = np.random.randn(HD)
W2 = np.random.randn(HD, OUTD)
b2 = np.random.randn(OUTD)

result = []
for url in urls:
    r = requests.get(url)
    soup = BeautifulSoup(r.content, 'html.parser')
    status = soup.find('div', class_='closed')
    titles = soup.find('h1', class_='section_hero__title')
    id= soup.find('p', class_='numer_id')
    result.append((url, status, titles, id))

import csv
with open('file.csv', mode='w') as file:
    writer = csv.writer(file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
    writer.writerow(['url','status','titles','id'])
    writer.writerows(result)

import pandas as pd

df = pd.DataFrame(data=result,columns = ['url','status','titles','id'])
df.to_csv('file.csv')

for span in zap.find_all('span', class_="sub", limit = 3):
    for link in span.find_all('a',href=True):
        print(link['href'])

final_df = pd.concat([df1,df2], ignore_index=True)
final_df.to_excel('имя файла')

df.to_csv(r'C:\pythonProject5\my_data.csv',mode='a',header=False)

columns = df.columns
empty_df = pd.DataFrame(columns=columns)
empty_df.to_csv(r'C:\pythonProject5\my_data.csv')

dfs = []
for i in range(длина):
    Здесь вы сравниваете и создаете датафрефм но вместо записи его в файл добавляете в список
    dfs.append(df)
final_df = pd.concat(dfs,ignore_index=True)
final_df.to_csv()