Python读取CSV数据绘制饼图遇TypeError报错求助

Hey there! Let's break down what's going wrong with your code and fix it step by step.

The Core Problem #

The main issue is that you're overwriting your lists instead of appending to them inside the loop. When you do Party = row[0], you're replacing the empty list with a single string (the party name from the current row). By the end of the loop, Party is just the last party name, Votes is just the last vote count (as a string), and plt.pie can't handle a single value—it needs a list of values to create slices. That's why you're getting the numpy.float64 has no len() error.

Corrected Code #

First, let's fix the list appending. We'll also convert the numeric columns (Seats and Votes) to integers since they're counts, and use a with statement to safely handle the file (it auto-closes when done):

import matplotlib.pyplot as plt
import csv

# Initialize empty lists
Party = []
Seats = []
Votes = []

# Use 'with' to open the file safely
with open("vote_results.csv", "r") as outfile:
    file = csv.reader(outfile)
    # Skip the header row
    next(file, None)
    
    # Append each row's data to the lists
    for row in file:
        Party.append(row[0])
        # Convert Seats and Votes to integers
        Seats.append(int(row[1]))
        Votes.append(int(row[2]))

# Create the pie chart
plt.pie(Votes, labels=Party, autopct='%1.1f%%')  # Add percentages for clarity
plt.title("Vote Distribution by Party")
plt.show()

Handling Space-Separated CSV #

If your CSV uses spaces instead of commas (like your example Party1 50 1000), you need to tell csv.reader to use spaces as the delimiter. Modify the csv.reader line like this:

file = csv.reader(outfile, delimiter=' ')

This will split each row correctly into the three columns.

Why This Works #

• Appending to lists: Now Party is a list of all party names, and Votes is a list of integers representing each party's vote count—exactly what plt.pie needs to create multiple slices.
• Numeric conversion: Converting row[1] and row[2] to integers ensures matplotlib can process the values correctly for the pie chart.
• Safe file handling: The with statement ensures the file is closed properly even if an error occurs.

Give this a try, and your pie chart should render correctly!

内容的提问来源于stack exchange，提问作者J. Smith