Concatenate two Dataframes

Question

I need to generate a new dataframe with the concatenation of two dataframes. The following code works, but it takes a long time to run.

df_concatena = pd.DataFrame()

for x in range(len(df)):
    for y in range(len(data)):
        df_concatena = df_concatena.append(pd.concat([df.iloc[x], data.iloc[y]]), ignore_index=True)

I tried to use apply but was unsuccessful.

Example df: df.Shape -> 81476

'Valor','Clase','Tempo'
44.99  , 'A'   , 5
61.49  , 'B'   , 8
102.24 , 'C'   , 6
51.07  , 'B'   , 8
32.78  , 'B'   , 12
30.05  , 'B'   , 10

Example date: date.Shape -> 21

'Dia_Semana','Faixa'
    0       , 'A'
    0       , 'B'  
    0       , 'C'  
    1       , 'A'  
    1       , 'B'  
    1       , 'C'  

For each df row, I need to add all 21 date lines.

Answer 1

You need to make the Cartesian product in those two dataframes. One option would be to use the merge, but it is necessary to create a key to connect these two dataframes, in case you call her k. And at the end of the one-man operation drop in that key. follow example code below:

import pandas as pd

df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
                     'B': ['B0', 'B1', 'B2', 'B3']})


df2 = pd.DataFrame({'C': ['C0', 'C1'],
                      'D': ['D0', 'D1']})

df1['k'] = 1
df2['k'] = 1

resultado = pd.merge(df1, df2, on=['k'])

resultado = resultado.drop(["k"],axis=1)
print(resultado.head(100))

##########
resultado
    A   B   C   D
0  A0  B0  C0  D0
1  A0  B0  C1  D1
2  A1  B1  C0  D0
3  A1  B1  C1  D1
4  A2  B2  C0  D0
5  A2  B2  C1  D1
6  A3  B3  C0  D0
7  A3  B3  C1  D1

Answer 2

Another option is to use the pd.concat:

dfA = pd.read_csv('yourfile_A.csv')
dfB = pd.read_csv('yourfile_B.csv')

df = pd.concat([dfA, dfB], axis=1)

Axis = 0 or Axis = 1 defines whether you want to join the dataframes per line (equal to append) or per column.