Concatenate MultiIndex Dataframes in Python

Question

I have 2 Multindex dataframes (date and ticker are indexes)

df_usdtbtc:

                         close
date          ticker                                                     
2017-12-31    USDT_BTC   13769
2018-01-01    USDT_BTC   13351

and df_ethbtc:

                         close
date          ticker                                                     
2017-12-31    USDT_ETH   736
2018-01-01    USDT_ETH   754

Is there any way to merge, concat or join these 2 dataframes to get as a result this dataframe :

                         close
date          ticker                                                     
2017-12-31    USDT_BTC   13769
              USDT_ETH   736
2018-01-01    USDT_BTC   13351
              USDT_ETH   754

To help set up the dataframes :

df_usdtbtc = {'dates':  [dtm(2018, 1, 1),dtm(2018, 1, 2)], 'ticker': ['USDT_BTC', 'USDT_BTC'],'close':[13769,13351]}
df_usdteth = {'dates':  [dtm(2018, 1, 1),dtm(2018, 1, 2)], 'ticker': ['USDT_ETH', 'USDT_ETH'],'close':[736,754]}
df_usdtbtc = pd.DataFrame(data=df_usdtbtc)
df_usdtbtc=df_usdtbtc.set_index(['dates','ticker'])
df_usdteth = pd.DataFrame(data=df_usdteth)
df_usdteth=df_usdteth.set_index(['dates','ticker'])

jezrael · Accepted Answer · 2018-05-08 17:11:03Z

1

Use concat or DataFrame.append with sort_index:

df = pd.concat([df_usdtbtc, df_ethbtc]).sort_index()

Or:

df = df_usdtbtc.append(df_ethbtc).sort_index()

df = pd.concat([df_usdtbtc, df_ethbtc]).sort_index()
print (df)
                     close
date       ticker         
2017-12-31 USDT_BTC  13769
           USDT_ETH    736
2018-01-01 USDT_BTC  13351
           USDT_ETH    754

answered May 8, 2018 at 17:11

jezrael

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