Google Sheets in Python with gspread
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This document discusses using Python and various libraries to interact with Google Sheets. It demonstrates how to import data from a Google Sheet using gspread, load it into a Pandas dataframe, write data back to Sheets from Pandas, and set up data validation rules in Sheets using gspread-formatting. The goals are to reduce friction between data systems, provide an Excel-like interface for data manipulation, and allow setting up validation to simplify data entry with little training since users are familiar with Excel.
![['Email', 'mike@example.com', 'maya@example.com',
'romba@example.net', 'boris@example.org']
Column name as part of response
worksheet.get_values()
Grab data as a list of lists
[
["Timestamp", "I'd like to contribute", ".."],
["18/05/2021 09:12:49", "Games", "Yes", "No", "20/05/2021", "mike@example.com"],
...
["18/05/2021 09:13:12", "Food", "Maybe", "Yes", "23/05/2021", "maya@example.com"],
["18/05/2021 09:13:32", "Let me know and I'll try to help", "No", "No",
"22/05/2021","romba@example.net",
],
]](https://image.slidesharecdn.com/gspreadpyljubljana-210525084054/85/Google-Sheets-in-Python-with-gspread-5-320.jpg)
![Loading data into pandas
import pandas as pd
import gspread
## https://github.com/robin900/gspread-dataframe
from gspread_dataframe import get_as_dataframe
gc = gspread.service_account()
worksheet = gc.open("Summer Potluck (Responses)").sheet1
df = get_as_dataframe(
worksheet,
parse_dates=True,
usecols=[0,5]
)
print(df.head())](https://image.slidesharecdn.com/gspreadpyljubljana-210525084054/85/Google-Sheets-in-Python-with-gspread-6-320.jpg)
![df = get_as_dataframe(
worksheet,
parse_dates=True,
usecols=[0,5]
)
0-indexed, only column 1 and 6
Timestamp Email
0 18/05/2021 09:12:49 mike@example.com
1 18/05/2021 09:13:12 maya@example.com
2 18/05/2021 09:13:32 romba@example.net
3 18/05/2021 09:14:03 boris@example.org
4 NaN NaN
Pandas DataFrame](https://image.slidesharecdn.com/gspreadpyljubljana-210525084054/85/Google-Sheets-in-Python-with-gspread-7-320.jpg)
![Writing to Sheets with Pandas
Python library: gspread-pandas
spread.df_to_sheet(df, index=False,
sheet='New Test Sheet', start='A2', replace=True)
spread.update_cells('A1', 'A1', ['Created by:', spread.email])
print(spread)
# <gspread_pandas.client.Spread - User: '<example_user>@gmail.com',
Spread: 'Example Spreadsheet', Sheet: 'New Test Sheet'>](https://image.slidesharecdn.com/gspreadpyljubljana-210525084054/85/Google-Sheets-in-Python-with-gspread-8-320.jpg)
![Python library: gspread-formatting
validation_rule = DataValidationRule(
BooleanCondition('ONE_OF_LIST',
['OK', 'FAIL', 'TO CHECK']),
showCustomUi=True
)
set_data_validation_for_cell_range(worksheet,
'C2:C100', validation_rule)](https://image.slidesharecdn.com/gspreadpyljubljana-210525084054/85/Google-Sheets-in-Python-with-gspread-10-320.jpg)
![Python library: gspread-formatting
validation_rule = DataValidationRule(
BooleanCondition("ONE_OF_RANGE", ["=Buildings!B2:$B30"]),
showCustomUi=True,
)
set_data_validation_for_cell_range(worksheet,
'B2:B100', validation_rule)](https://image.slidesharecdn.com/gspreadpyljubljana-210525084054/85/Google-Sheets-in-Python-with-gspread-11-320.jpg)
Google Sheets in Python with gspread
- 1. Jure Čuhalev Google Sheets in Python with gspread Reducing friction between data systems
- 2. Problem: Users love to use Excel-like interface for data manipulation Solution: Introduce multiplayer Excel: Google Sheets
- 3. Basic usage of gspread in Python
- 4. import gspread gc = gspread.service_account() worksheet = gc.open("Summer Potluck (Responses)").sheet1 values_list = worksheet.col_values(6) print(values_list) Google Service Account with access to this Sheet Use human friendly names 1-indexed because Excel 🙄
- 5. ['Email', 'mike@example.com', 'maya@example.com', 'romba@example.net', 'boris@example.org'] Column name as part of response worksheet.get_values() Grab data as a list of lists [ ["Timestamp", "I'd like to contribute", ".."], ["18/05/2021 09:12:49", "Games", "Yes", "No", "20/05/2021", "mike@example.com"], ... ["18/05/2021 09:13:12", "Food", "Maybe", "Yes", "23/05/2021", "maya@example.com"], ["18/05/2021 09:13:32", "Let me know and I'll try to help", "No", "No", "22/05/2021","romba@example.net", ], ]
- 6. Loading data into pandas import pandas as pd import gspread ## https://github.com/robin900/gspread-dataframe from gspread_dataframe import get_as_dataframe gc = gspread.service_account() worksheet = gc.open("Summer Potluck (Responses)").sheet1 df = get_as_dataframe( worksheet, parse_dates=True, usecols=[0,5] ) print(df.head())
- 7. df = get_as_dataframe( worksheet, parse_dates=True, usecols=[0,5] ) 0-indexed, only column 1 and 6 Timestamp Email 0 18/05/2021 09:12:49 mike@example.com 1 18/05/2021 09:13:12 maya@example.com 2 18/05/2021 09:13:32 romba@example.net 3 18/05/2021 09:14:03 boris@example.org 4 NaN NaN Pandas DataFrame
- 8. Writing to Sheets with Pandas Python library: gspread-pandas spread.df_to_sheet(df, index=False, sheet='New Test Sheet', start='A2', replace=True) spread.update_cells('A1', 'A1', ['Created by:', spread.email]) print(spread) # <gspread_pandas.client.Spread - User: '<example_user>@gmail.com', Spread: 'Example Spreadsheet', Sheet: 'New Test Sheet'>
- 9. Sheets - Data Validation
- 10. Python library: gspread-formatting validation_rule = DataValidationRule( BooleanCondition('ONE_OF_LIST', ['OK', 'FAIL', 'TO CHECK']), showCustomUi=True ) set_data_validation_for_cell_range(worksheet, 'C2:C100', validation_rule)
- 11. Python library: gspread-formatting validation_rule = DataValidationRule( BooleanCondition("ONE_OF_RANGE", ["=Buildings!B2:$B30"]), showCustomUi=True, ) set_data_validation_for_cell_range(worksheet, 'B2:B100', validation_rule)
- 13. Administrative data with different fields Type of Document Type of Institution Type of Repository Type of Education
- 14. Python sets up Data Validation Sheets Drop down data with correct choices Data validation Low amount of training needed because users already feel comfortable in Excel
- 15. Possible next steps - Callback to apply new data on server - Use it to generate embeded charts - PivotTable reports based on imported data (no code access for business analytics)
- 16. Slides and code at jurecuhalev.com Libraries used: gspread, gspread-dataframe, gspread-pandas, gspread-formatting Q/A Plus: • interviews with interesting people from IT • how I use code to automate business • tips on sourdough bread baking