将DataFrame按‘列‘转换为NumPy数组

柔光的暖阳◎ 2024-02-21 09:34 46阅读 0赞

\# 使用.values.T 按'列'转换为NumPy数组  
  
\# 遍历DataFrame的'列'并逐一填充NumPy数组

\# 使用\[df\[col\].to\_numpy() for col in df.columns\]每列转换为NumPy数组

import pandas as pd
    import numpy as np
    
    # 创建一个示例DataFrame
    data = {'A': [7, 2, 3], 'B': [3, 5, 6], 'C': [0, 8, 9]}
    df = pd.DataFrame(data)
    
    # 获取行数和列数
    num_rows, num_columns = df.shape
    
    # 打印结果
    print("行数:", num_rows)
    print("列数:", num_columns)
    
    
    # 使用.values.T 将DataFrame按'列'转换为NumPy数组
    numpy_array = df.T.values
    
    # 打印结果
    print(numpy_array)
    
    
    # 将DataFrame按列转换为numpy数组,遍历DataFrame的'列'并逐一填充NumPy数组
    numpy_data = np.zeros((num_rows,num_columns))
    col = df.columns
    for i,j in enumerate(col):
        numpy_data[i]=df[j]
    print(numpy_data)

import pandas as pd
    
    
    # 创建一个示例DataFrame
    data = {'A': [7, 2, 3], 'B': [9, 5, 6], 'C': [6, 8, 9]}
    df = pd.DataFrame(data)
    
    # 使用to_numpy()方法按列分别将DataFrame的数据转换为NumPy数组
    numpy_arrays = [df[col].to_numpy() for col in df.columns]
    
    print(numpy_arrays)
    
    
    # 打印每列的NumPy数组
    for i, col in enumerate(df.columns):
        print(f"NumPy array for column {col} (Index {i}):\n{numpy_arrays[i]}")
    
    # [array([7, 2, 3], dtype=int64), array([9, 5, 6], dtype=int64), array([6, 8, 9], dtype=int64)]
    # NumPy array for column A (Index 0):
    # [7 2 3]
    # NumPy array for column B (Index 1):
    # [9 5 6]
    # NumPy array for column C (Index 2):
    # [6 8 9]
    # [Finished in 3.9s]