[英]Python Pandas Concat list of Dataframes With Different Columns and Same Rows
[英]Python: concat rows of two dataframes where not all columns are the same
我有兩個數據框:
編輯:
df1 = pd.DataFrame(index = [0,1,2], columns=['timestamp', 'order_id', 'account_id', 'USD', 'CAD'])
df1['timestamp']=['2022-01-01','2022-01-02','2022-01-03']
df1['account_id']=['usdcad','usdcad','usdcad']
df1['order_id']=['11233123','12313213','12341242']
df1['USD'] = [1,2,3]
df1['CAD'] = [4,5,6]
df1:
timestamp account_id order_id USD CAD
0 2022-01-01 usdcad 11233123 1 4
1 2022-01-02 usdcad 12313213 2 5
2 2022-01-03 usdcad 12341242 3 6
df2 = pd.DataFrame(index = [0,1], columns = ['timestamp','account_id', 'currency','balance'])
df2['timestamp']=['2021-12-21','2021-12-21']
df2['account_id']=['usdcad','usdcad']
df2['currency'] = ['USD', 'CAD']
df2['balance'] = [2,3]
df2:
timestamp account_id currency balance
0 2021-12-21 usdcad USD 2
1 2021-12-21 usdcad CAD 3
我想在索引 0 處向 df1 添加一行,並根據貨幣用 df2 的余額填充該行。 所以最終的 df 應該是這樣的:
df:
timestamp account_id order_id USD CAD
0 0 0 0 2 3
1 2022-01-01 usdcad 11233123 1 4
2 2022-01-02 usdcad 12313213 2 5
3 2022-01-03 usdcad 12341242 3 6
我怎樣才能以 pythonic 方式做到這一點? 謝謝
將df2
的索引設置為currency
然后將索引轉置為列,然后 append 這個 dataframe 和df1
df_out = df2.set_index('currency').T.append(df1, ignore_index=True).fillna(0)
print(df_out)
USD CAD order_id
0 2 3 0
1 1 4 11233123
2 2 5 12313213
3 3 6 12341242
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