怎么用python分析数据

<code class="python">import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns</code>

<code class="python">data = pd.read_csv('data.csv')  # 从 CSV 文件读取数据
data = pd.read_sql_query('SELECT * FROM table', conn)  # 从数据库读取数据</code>

<code class="python">print(data.head())  # 查看数据的第一几行
print(data.info())  # 显示数据信息，包括数据类型、空值等</code>

<code class="python">data = data.dropna()  # 删除所有包含 NaN 的行
data = data[data['column'] < 1000]  # 删除特定列中值大于 1000 的行</code>

<code class="python">data['new_column'] = data['old_column'] + 10  # 创建一个新列
data['date'] = pd.to_datetime(data['date'])  # 将字符串日期转换为 datetime 对象</code>

<code class="python">print(data.mean())  # 计算所有数值列的平均值
print(data.groupby('group').sum())  # 按组对列求和</code>

<code class="python">sns.barplot(x='group', y='value', data=data)  # 创建条形图
plt.scatter(x='x', y='y', data=data)  # 创建散点图</code>

<code class="python">from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(X, y)  # 模型拟合</code>