This post will demo 3 Ways to save pandas data.
Use to_csv
method of DataFrame to transfer DataFrame to CSV file.
And use files.download
method to download the file programatically.
from google.colab import files
df.to_csv('output.csv', encoding = 'utf-8-sig')
files.download('output.csv')
First, it needs to import drive
and execute mount
method.
Here will mount my google drive in this path /content/drive
.
Second, use open
to open a file which will be a parameter of to_csv
method.
from google.colab import drive
drive.mount('/content/drive')
path = '/content/drive/My Drive/outpur.csv'
with open(path, 'w', encoding = 'utf-8-sig') as f:
df.to_csv(f)
Here will use gspread
library to help me to deal with google spreadsheet.
So, it needs to import gspread
and do the Authorization.
And then, I need a spreadsheet for saving data, so I prepared a spreadsheet and get it's key(or id).
In the following code, I just save all data into spreadsheet begin at sheet1!A1 cell.
!pip install gspread
from google.colab import auth
from oauth2client.client import GoogleCredentials
import gspread
import pandas as pd
# Auth
auth.authenticate_user()
gc = gspread.authorize(GoogleCredentials.get_application_default())
spreadsheet_key = 'my_spreadsheet_key'
workbook = gc.open_by_key(spreadsheet_key)
workbook.values_update(
'sheet!A1',
params={
'valueInputOption': 'USER_ENTERED'
},
body={
'values': [df.columns.values.tolist()] + df.values.tolist()
}
)
That's all.
I hope it will help you.