这可能是因为数据类型，你可以尝试这个更新的代码，我为你开发的，但如果我知道什么是数据或共享的一部分，我可以帮助你更好

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Read the dataset
dataFrame = pd.read_csv('dataset.csv', sep=',')
dataFrame.replace('', np.nan, inplace=True)  # Apply the NaN replacement to the DataFrame

# Create new smaller dataset
roomsDF = pd.DataFrame(dataFrame[['Price', 'Living Rooms', 'Halls', 'Bathrooms']])
roomsDF.dropna(axis='rows', inplace=True)  # Drop rows with missing values

# Convert columns to numerical data type
roomsDF['Living Rooms'] = pd.to_numeric(roomsDF['Living Rooms'])
roomsDF['Halls'] = pd.to_numeric(roomsDF['Halls'])
roomsDF['Bathrooms'] = pd.to_numeric(roomsDF['Bathrooms'])

# Plotting
plt.figure(figsize=(12, 4))

plt.subplot(131)
plt.bar(roomsDF['Living Rooms'], roomsDF['Price'], color='darkgreen')
plt.xlabel('Living Rooms')
plt.ylabel('Price')

plt.subplot(132)
plt.bar(roomsDF['Halls'], roomsDF['Price'], color='limegreen')
plt.xlabel('Halls')
plt.ylabel('Price')

plt.subplot(133)
plt.bar(roomsDF['Bathrooms'], roomsDF['Price'], color='seagreen')
plt.xlabel('Bathrooms')
plt.ylabel('Price')

plt.tight_layout()  # Adjust subplot spacing
plt.savefig('Picture.png')

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在这里我也需要使用groupby。没有groupby，它只是显示一些随机的东西。

plotData = pd.DataFrame(dataFrame.groupby(['Living Rooms'])['Price'].mean()).reset_index()
plt.bar(plotData['Living Rooms'], plotData['Price'], color='darkgreen')

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