构建智慧的大数据分析平台

import pandas as pd

# 读取CSV文件

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

print(data.head())

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# 去除重复行

data.drop_duplicates(inplace=True)

# 删除缺失值过多的列

data.dropna(axis=1, thresh=len(data)*0.7, inplace=True)

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# 计算某个字段的平均值

average_value = data['field'].mean()

print(f"Average value: {average_value}")

# 找出最大值

max_value = data['field'].max()

print(f"Maximum value: {max_value}")

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import matplotlib.pyplot as plt

# 绘制柱状图

plt.figure(figsize=(10,6))

plt.bar(data['category'], data['value'])

plt.title('Category vs Value')

plt.xlabel('Category')

plt.ylabel('Value')

plt.show()

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from sklearn.linear_model import LinearRegression

# 准备训练数据

X = data[['feature1', 'feature2']]

y = data['target']

# 创建模型

model = LinearRegression()

model.fit(X, y)

# 预测

predictions = model.predict(X)

print(predictions)

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