我有兩個DataFrames；df1并且df2它們都包含大部分NaN值。它們在資料集中的相同位置具有非 NaN 值。基于這兩者DataFrames，我想df為所有值創建一列df1，一列用于df2，以便我擁有來自兩者的值對DataFrames。
在這里我創建了一個簡單的例子：
df1:
01K 02K 03K 04K
Dates
2021-01-01 NaN NaN NaN NaN
2021-01-02 NaN 2.5 NaN NaN
2021-01-03 NaN NaN 4.1 NaN
2021-01-04 8.2 NaN 9.0 NaN
2021-01-05 NaN 1.2 NaN NaN
2021-01-06 NaN NaN NaN NaN
df2:
01K 02K 03K 04K
Dates
2021-01-01 NaN NaN NaN NaN
2021-01-02 NaN 0.6 NaN NaN
2021-01-03 NaN NaN 0.4 NaN
2021-01-04 0.1 NaN 0.2 NaN
2021-01-05 NaN 0.2 NaN NaN
2021-01-06 NaN NaN NaN NaN
df:
df1 df2
0 8.2 0.1
1 2.5 0.6
2 1.2 0.2
3 4.1 0.4
4 9.0 0.2
為了重現性：
df1 = pd.DataFrame({
'Dates':['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04', '2021-01-05', '2021-01-06'],
'01K':[np.nan, np.nan, np.nan, 8.2, np.nan, np.nan],
'02K':[np.nan, 2.5, np.nan, np.nan, 1.2, np.nan],
'03K':[np.nan, np.nan, 4.1, 9.0, np.nan, np.nan],
'04K':[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan]})
df1 = df1.set_index('Dates')
df2 = pd.DataFrame({
'Dates':['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04', '2021-01-05', '2021-01-06'],
'01K':[np.nan, np.nan, np.nan, 0.1, np.nan, np.nan],
'02K':[np.nan, 0.6, np.nan, np.nan, 0.2, np.nan],
'03K':[np.nan, np.nan, 0.4, 0.2, np.nan, np.nan],
'04K':[np.nan, np.nan, np.nan, np.nan, np.nan, np.nan]})
df2 = df2.set_index('Dates')
非常感謝您的建議
uj5u.com熱心網友回復：
您可以使用stack來擺脫 nan 的：
pd.DataFrame({'df1': df1.stack(), 'df2': df2.stack()})
輸出：
df1 df2
Dates
2021-01-02 02K 2.5 0.6
2021-01-03 03K 4.1 0.4
2021-01-04 01K 8.2 0.1
03K 9.0 0.2
2021-01-05 02K 1.2 0.2
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