Перевернуть или транспонировать DataFrame

from tkinter import Tk
from tkinter.filedialog import askopenfilename
import pandas as pd
import xlwt as xlwt
 
def filename():
    Tk().withdraw()  # we don't want a full GUI, so keep the root window from appearing
    strn = askopenfilename(filetypes=(("CSV files", "*.csv"),))  # show an "Open" dialog box and return the path to the selected file
    return (strn)
 
val = filename()
x = val.replace('/', '\\')
df = pd.read_csv(x, delimiter=',', names=['data', 'time', 'Open', 'Max', 'Min', 'Close', 'Volume'])
 
df = df.drop(['Max','Min', 'Volume'], axis=1)
df['O-C'] = df.Open - df.Close
df = df.drop(['Open','Close'], axis=1)
# create excel writer object
writer =d.ExcelWriter('C:/Users/Admin/Documents/PLoad/data/output.xlsx')
# write dataframe to excel
df.to_excel(writer)
# save the excel
writer.save()

 # -*- coding: utf-8 -*-
"""Untitled2.ipynb
 
Automatically generated by Colaboratory.
 
Original file is located at
    https://colab.research.google.com/drive/1uns-JooDaT0Ng83GXRE1aTSkBrrhiVrU
"""
 
import pandas as pd
 
df = pd.read_csv('/content/drive/MyDrive/EURUSD1_1.csv', header=None)
df.columns = ['date', 'time', 'open', 'max', 'min', 'close', 'val']
df['diff'] = df['open'] - df['close']
df['date_hour'] = df['date'] + ' ' + df['time'].map(lambda x: x[:2]) #pd.to_timedelta(df['time'].dt.time.astype(str))
df['minutes'] = df['time'].map(lambda x: x[-2:])
 
df1 = df[['date_hour', 'minutes', 'diff']]
df1 = df1.set_index(['date_hour', 'minutes'], drop=True)
df1 = df1.unstack(level=-1)
print(df1)

 import pandas as pd
from datetime import datetime
 
cd = lambda x: datetime.strptime(str(x), '%H:%M')
df = pd.read_csv('/content/drive/MyDrive/EURUSD1_1.csv', header=None)#, parse_dates=[0, 1])
df.columns = ['date', 'time', 'open', 'max', 'min', 'close', 'val']
df['diff'] = df['open'] - df['close']
df['date_hour'] = df['date'] + ' ' + df['time'].map(lambda x: x[:2]) #pd.to_timedelta(df['time'].dt.time.astype(str))
df['minutes'] = df['time'].map(lambda x: x[-2:])
 
df1 = df[['date_hour', 'minutes', 'diff']]
df1 = df1.set_index(['date_hour', 'minutes'], drop=True)
df1 = df1.unstack(level=-1)
 
#######################################
n = len(df1)
df1.index = range(1, 2*n, 2)
df1 = df1.droplevel(0, axis=1)
df2 = pd.DataFrame([df1.columns.tolist() for _ in range(n)],
                   index = range(0, 2*n, 2),
                   columns = df1.columns)
df_res = pd.concat([df1, df2]).sort_index()
df_res