how to convert pandas groupby output to separate excel sheet?-CodePudding

I have created a timestamp of 10 days of hourly data and then create 2 random columns with random values.

import pandas as pd
import numpy as np
timestamp = pd.date_range('01/01/2020 00:00','01/10/2020 23:00', freq = '1H')
arr1 = np.random.randint(100,200,(len(timestamp)))
arr2 = np.random.randint(100,200,(len(timestamp)))

the created the dataframe of these two arrays with col1 and col2 as columns and with timestamp as an index.

dic1 = {'col1':arr1,'col2':arr2}
df = pd.DataFrame(dic1, index=timestamp)

After that, I used the pandas groupby function to group them by days and I wanted to create the excel output of each group ( 10 excel outputs for 10 days).

df2 = df.groupby(pd.Grouper(freq='D'))
for idx, i in enumerate(df2):
   df = pd.Dataframe(i)
   df.to_csv(str(idx) '.csv')

but this gives out very strange output, 10 excel files are there but no values in them. Can someone please help? Desired output for day 1:

similarly, for every day this type of excel should be generated.

CodePudding user response：

When you do for idx, i in enumerate(df2), each i is a pair group_key, data. Try:

for g, data in df.groupby(...):
    data.to_csv(str(g)   '.csv')

If you really want enumerate:

for idx, (g, data) in enumerate(df.groupby(...)):
    data.to_csv(str(idx)   '.csv')

CodePudding user response：

If you iterate a .groupby, you get a 2-tuple where the first element is the group key and the second one the group data, so you need something like:

df2 = df.groupby(pd.Grouper(freq='D'))
for idx, (_, sdf) in enumerate(df2):
   sdf.to_csv(str(idx)   '.csv')