大数据平台与信息处理：对话式探讨

# Python代码示例：数据清洗

import pandas as pd

def clean_data(df):

df = df.dropna() # 删除缺失值

df = df[df['age'] > 0] # 过滤年龄小于等于0的记录

return df

data = pd.read_csv('data.csv')

cleaned_data = clean_data(data)

cleaned_data.to_csv('cleaned_data.csv', index=False)

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# Python代码示例：数据分析

import pandas as pd

import matplotlib.pyplot as plt

data = pd.read_csv('cleaned_data.csv')

print(data.describe()) # 输出数据描述性统计信息

# 绘制年龄分布图

plt.hist(data['age'], bins=20)

plt.title('Age Distribution')

plt.xlabel('Age')

plt.ylabel('Count')

plt.show()

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