我有 3 個(gè)數(shù)據(jù)框：dataframe_1: A B C D 1 E 2 F 3 G 4 Hdataframe_2: A B C D 5 I 6 J 7 K 8 Ldf_columns = ['username', 'reason']dataframe_3 = pd.DataFrame(columns=df_columns)我想將所有行添加到dataframe_1Butdataframe_2中dataframe_3 ，但映射如下：dataframe_3.append(dataframe_1['A','reason 1'])dataframe_3.append(dataframe_2['A','reason 2'])最終得到： dataframe_3: username reason 1 reason 1 3 reason 1 5 reason 2 7 reason 2 因此，本質(zhì)上使用列A并將其映射到username每個(gè)數(shù)據(jù)框并具有特定原因。關(guān)于如何實(shí)現(xiàn)這一目標(biāo)的任何想法？
2 回答
POPMUISE
TA貢獻(xiàn)1765條經(jīng)驗(yàn) 獲得超5個(gè)贊
你的意思是：
(pd.concat((df1[['A']].assign(reason='reason 1'),
df2[['A']].assign(reason='reason 2'))
)
.rename(columns={'A':'username'})
)
繁星點(diǎn)點(diǎn)滴滴
TA貢獻(xiàn)1803條經(jīng)驗(yàn) 獲得超3個(gè)贊
這對我有用：
import pandas as pd
dataframe_1 = pd.DataFrame(
{'A': [1, 3], 'B': ['E', 'G'], 'C': [2, 4], 'D': ['F', 'H']})
dataframe_2 = pd.DataFrame(
{'A': [5, 7], 'B': ['I', 'K'], 'C': [6, 8], 'D': ['J', 'L']})
df_columns = ['username', 'reason']
dataframe_3 = pd.DataFrame(columns=df_columns)
for count, number in enumerate(dataframe_1['A']):
dataframe_3.at[count, 'username'] = number
dataframe_3.at[count, 'reason'] = 'reason 1'
for count, number in enumerate(dataframe_2['A'], count + 1):
dataframe_3.at[count, 'username'] = number
dataframe_3.at[count, 'reason'] = 'reason 2'
print(dataframe_3)
輸出：
username reason
0 1 reason 1
1 3 reason 1
2 5 reason 2
3 7 reason 2
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