熊貓數據框，獲取每行的最近日期

Question

我試圖遍歷每一行（iterrow？）並找到最新日期（sort函數？）並將其放在“ G”列中

我在組合迭代功能和排序功能時遇到麻煩。

    A       B           C           D           E           F           G
0   1       20171018    20171019    20171001    20171002    id_123      
1   2       NaN         20171005    20171006    20171003    id_234      
2   3       NaN         NaN         20171019    20171020    id_345      
3   4       NaN         NaN         NaN         20171021    id_456      

期望的輸出

    A       B           C           D           E           F           G
0   1       20171018    20171019    20171001    20171002    id_123      20171019
1   2       NaN         20171005    20171006    20171003    id_234      20171006
2   3       NaN         NaN         20171019    20171020    id_345      20171020
3   4       NaN         NaN         NaN         20171021    id_456      20171021

這是生成數據框的代碼

data2 = {'A': [1, 2, 3, 4], 
        'B': ['20171018', '', '', ''], 
        'C': ['20171019', '20171005', '', ''],
        'D': ['20171001', '20171006', '20171019', ''],
        'E': ['20171002', '20171003', '20171020', '20171021'],
        'F': ['id_123','id_234','id_345','id_456'],
        'G': ['','','','']
        }
df3 = pd.DataFrame(data2)

編輯：我已經使用datetime轉換了日期列

Answer 1

您可以在數據框上使用.max()方法來獲取最新日期。 您將需要傳遞參數axis=1以使其沿每一行計算最大值。

import pandas as pd

data = {'A': [1, 2, 3, 4],
        'B': ['20171018', '', '', ''],
        'C': ['20171019', '20171005', '', ''],
        'D': ['20171001', '20171006', '20171019', ''],
        'E': ['20171002', '20171003', '20171020', '20171021'],
        'F': ['id_123','id_234','id_345','id_456']
        }
df = pd.DataFrame(data)

# convert to datetimes
for c in 'BCDE':
    df[c] = pd.to_datetime(df[c])

# create a new column
df['G'] = df[['B','C','D','E']].max(axis=1)
print(df)

   A          B          C          D          E       F          G
0  1 2017-10-18 2017-10-19 2017-10-01 2017-10-02  id_123 2017-10-19
1  2        NaT 2017-10-05 2017-10-06 2017-10-03  id_234 2017-10-06
2  3        NaT        NaT 2017-10-19 2017-10-20  id_345 2017-10-20
3  4        NaT        NaT        NaT 2017-10-21  id_456 2017-10-21