如果我有這些數據框df1 = pd.DataFrame({'index': [1,2,3,4], 'col1': ['a','b','c','d'], 'col2': ['h','e','l','p']})df2 = pd.DataFrame({'index': [1,2,3,4], 'col1': ['a','e','f','d'], 'col2': ['h','e','lp','p']})df1 index col1 col20 1 a h1 2 b e2 3 c l3 4 d pdf2 index col1 col20 1 a h1 2 e e2 3 f lp3 4 d p我想合并它們并查看行是否不同并得到這樣的輸出 index col1 col1_validation col2 col2_validation0 1 a True h True1 2 b False e True2 3 c False l False3 4 d True p True我怎樣才能做到這一點？
2 回答
犯罪嫌疑人X
TA貢獻2080條經驗 獲得超4個贊
看起來col1和col2您的“合并”數據框只是取自df1. 在這種情況下，您可以簡單地比較原始數據幀之間的 , 并將它們添加為列col1：col2
cols = ["col1", "col2"]
val_cols = ["col1_validation", "col2_validation"]
# (optional) new dataframe, so you don't mutate df1
df = df1.copy()
new_cols = (df1[cols] == df2[cols])
df[val_cols] = new_cols
泛舟湖上清波郎朗
TA貢獻1818條經驗 獲得超3個贊
您可以使用類似于以下內容的方式合并和比較兩個數據框：
df1 = pd.DataFrame({'index': [1,2,3,4],
'col1': ['a','b','c','d'],
'col2': ['h','e','l','p']})
df2 = pd.DataFrame({'index': [1,2,3,4],
'col1': ['a','e','f','d'],
'col2': ['h','e','lp','p']})
# give columns unique name when merging
df1.columns = df1.columns + '_df1'
df2.columns = df2.columns + '_df2'
# merge/combine data frames
combined = pd.concat([df1, df2], axis = 1)
# add calculated columns
combined['col1_validation'] = combined['col1_df1'] == combined['col1_df2']
combined['col12validation'] = combined['col2_df1'] == combined['col2_df2']
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