Dataset到DataFrame的转换

import pandas as pd

# 读取CSV文件
df = pd.read_csv('path_to_your_file.csv')

# 现在df是一个DataFrame对象
print(df.head())  # 打印前五行数据

import pandas as pd

# 读取Excel文件
df = pd.read_excel('path_to_your_file.xlsx')

# 现在df是一个DataFrame对象
print(df.head())  # 打印前五行数据

from pyspark.sql import SparkSession

# 初始化SparkSession
spark = SparkSession.builder.appName('example').getOrCreate()

# 从CSV文件读取数据为DataFrame
df = spark.read.csv('path_to_your_file.csv', inferSchema=True, header=True)

# 显示DataFrame
df.show()

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charles'],
        'Age': [25, 30, 35],
        'City': ['New York', 'Los Angeles', 'Chicago']}

df = pd.DataFrame(data)

print(df)

import pandas as pd

data = [['Alice', 25, 'New York'],
        ['Bob', 30, 'Los Angeles'],
        ['Charles', 35, 'Chicago']]

df = pd.DataFrame(data, columns=['Name', 'Age', 'City'])

print(df)