使用Python模块进行数据处理的详细步骤

pip install pandas

import pandas as pd

# 创建一个 DataFrame
data = {
    "Name": ["Alice", "Bob", "Charlie"],
    "Age": [25, 30, 35],
    "City": ["New York", "Los Angeles", "Chicago"]
}

df = pd.DataFrame(data)

# 查看 DataFrame
print(df)

# 数据清洗
# 删除重复行
df.drop_duplicates(inplace=True)

# 填充缺失值
df.fillna(value={"Age": 0, "City": "Unknown"}, inplace=True)

# 数据筛选
young_people = df[df["Age"] < 30]
print(young_people)

# 数据排序
sorted_df = df.sort_values(by="Age", ascending=False)
print(sorted_df)

# 数据聚合
average_age = df["Age"].mean()
print(f"Average Age: {average_age}")

# 数据导出
df.to_csv("output.csv", index=False)

pip install numpy

import numpy as np

# 创建一个 NumPy 数组
data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

# 查看数组
print(data)

# 数值计算
mean_value = np.mean(data)
print(f"Mean Value: {mean_value}")

# 数组切片
sub_array = data[1:, :2]
print(sub_array)

# 数组操作
data_squared = data ** 2
print(data_squared)

# 数据导出
np.savetxt("output.txt", data, fmt="%d")

pip install matplotlib

import matplotlib.pyplot as plt

# 创建数据
x = [1, 2, 3, 4, 5]
y = [2, 3, 5, 7, 11]

# 绘制折线图
plt.plot(x, y, label="Line 1")
plt.title("Line Plot Example")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.legend()
plt.show()

# 绘制柱状图
categories = ["A", "B", "C", "D", "E"]
values = [10, 15, 7, 12, 20]

plt.bar(categories, values, color="skyblue")
plt.title("Bar Chart Example")
plt.xlabel("Categories")
plt.ylabel("Values")
plt.show()

pip install scikit-learn

from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
import numpy as np

# 创建数据
X = np.array([[1], [2], [3], [4], [5]])
y = np.array([2, 4, 6, 8, 10])

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 创建线性回归模型
model = LinearRegression()

# 训练模型
model.fit(X_train, y_train)

# 进行预测
y_pred = model.predict(X_test)

# 评估模型
mse = mean_squared_error(y_test, y_pred)
print(f"Mean Squared Error: {mse}")

import pandas as pd
import matplotlib.pyplot as plt

# 创建一个 DataFrame
data = {
    "Name": ["Alice", "Bob", "Charlie"],
    "Age": [25, 30, 35],
    "City": ["New York", "Los Angeles", "Chicago"]
}

df = pd.DataFrame(data)

# 数据清洗
df.drop_duplicates(inplace=True)
df.fillna(value={"Age": 0, "City": "Unknown"}, inplace=True)

# 数据筛选
young_people = df[df["Age"] < 30]

# 数据排序
sorted_df = df.sort_values(by="Age", ascending=False)

# 数据可视化
plt.figure(figsize=(10, 6))
plt.bar(sorted_df["Name"], sorted_df["Age"], color="skyblue")
plt.title("Age Distribution")
plt.xlabel("Name")
plt.ylabel("Age")
plt.show()