Since you’ve moved your Excel data to Google Sheets, here are two reliable methods to adapt your code to pull that cloud-based data—both will integrate seamlessly with your existing pandas/numpy workflow.

Method 1: Using gspread (Recommended for private sheets) #

This method uses Google’s official Sheets API, so it’s ideal if you need to keep your sheet private and secure.

Step 1: Set up credentials #

• Create a new project in your Google Cloud dashboard.
• Enable the Google Sheets API for this project.
• Generate a service account, then download the JSON credentials file associated with it.
• Share your target Google Sheet with the email address listed in the credentials JSON (grant "Viewer" access at minimum).

Step 2: Install required packages #

Run these commands in your terminal:

pip install gspread pandas numpy

Step 3: Update your code to read the sheet #

Replace your local Excel reading code with this snippet—your existing data processing logic will work unchanged after this:

import gspread
import pandas as pd
import numpy as np

# Authenticate with your credentials file
gc = gspread.service_account(filename='path/to/your/credentials.json')

# Open the sheet (use the exact name of your Google Sheet)
# For specific worksheets, use .worksheet("Worksheet Name") instead of .sheet1
sheet = gc.open('Your Google Sheet Name').sheet1

# Convert sheet data to a pandas DataFrame (matches your original df structure)
df = pd.DataFrame(sheet.get_all_records())

# Your existing code starts here
num = np.array([df['NUM']])
canal = np.array([df['CANAL']])
cluster = np.array([df['CLUSTER']])
region = np.array([df['REGION']])

# ... your后续数据处理代码 and visualization code remains exactly the same ...

Method 2: Using pandas with a public sheet link (Simpler for public data) #

If you don’t mind making your sheet accessible to anyone with the link, this method skips API setup entirely.

Step 1: Make your sheet public #

• Open your Google Sheet, click "Share" → "Get link" → set access to "Anyone with the link" (Viewer permission is sufficient).
• Copy the share URL, and extract the unique sheet ID (the long string between /d/ and /edit).

Step 2: Read directly with pandas #

Replace your local pd.read_excel call with this:

import pandas as pd
import numpy as np

# Replace {SHEET_ID} with your actual sheet ID from the share URL
sheet_export_url = "https://docs.google.com/spreadsheets/d/{SHEET_ID}/export?format=xlsx"
df = pd.read_excel(sheet_export_url)

# Your existing data processing code works exactly as before
num = np.array([df['NUM']])
# ... rest of your code ...

Quick Tips #

• Both methods produce a df DataFrame identical to the one from your local Excel file, so all your loops, dictionaries, and numpy operations will run without modifications.
• For multi-worksheet sheets: In gspread, use gc.open("Sheet Name").worksheet("Specific Tab Name"). In the pandas method, add sheet_name="Tab Name" to the pd.read_excel call.

内容的提问来源于stack exchange，提问作者Joaquin