Python Pandas - 使用基于索引、列的字典更新行

Ara*_*eel 5 dictionary python-3.x pandas

我有一个包含空列和相应字典的数据框,我想根据索引、列更新空列:

import pandas as pd    
import numpy as np

dataframe = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9], [4, 6, 2], [3, 4, 1]])
dataframe.columns = ['x', 'y', 'z']
additional_cols = ['a', 'b', 'c']

for col in additional_cols:
     dataframe[col] = np.nan

    x   y   z   a  b  c
0   1   2   3           
1   4   5   6           
2   7   8   9           
3   4   6   2           
4   3   4   1           

for row, column in x.iterrows():
    #caluclations to return dictionary y
    y = {"a": 5, "b": 6, "c": 7}
    df.loc[row, :].map(y)
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基本上在使用 x、y、z 列执行计算后,我想更新同一行的 a、b、c 列:)

Ara*_*eel 5

我可以使用这样的函数,但就 pandas 库和 DataFrame 对象的方法而言,我不确定:

def update_row_with_dict(dictionary, dataframe, index):  
    for key in dictionary.keys():  
        dataframe.loc[index, key] = dictionary.get(key)
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