Example 1: concat columns pandas dataframe
In [1]: df1 = pd.DataFrame(
...: {
...: "A": ["A0", "A1", "A2", "A3"],
...: "B": ["B0", "B1", "B2", "B3"],
...: "C": ["C0", "C1", "C2", "C3"],
...: "D": ["D0", "D1", "D2", "D3"],
...: },
...: index=[0, 1, 2, 3],
...: )
In [8]: df4 = pd.DataFrame(
...: {
...: "B": ["B2", "B3", "B6", "B7"],
...: "D": ["D2", "D3", "D6", "D7"],
...: "F": ["F2", "F3", "F6", "F7"],
...: },
...: index=[2, 3, 6, 7],
...: )
...:
In [9]: result = pd.concat([df1, df4], axis=1)
# This will merge columns of both the dataframes
Example 2: concat dataframe from list of dataframe
import pandas as pd
df = pd.concat(list_of_dataframes)
Example 3: merge two columns pandas
df["period"] = df["Year"] + df["quarter"]
Example 4: concat pandas python
>>> s1 = pd.Series(['a', 'b'])
>>> s2 = pd.Series(['c', 'd'])
>>> pd.concat([s1, s2])
0 a
1 b
0 c
1 d
dtype: object
Example 5: pandas concat and reset index
train_df = pd.concat(train_class_df_list, ignore_index=True)
Example 6: dataframe concatenate
# Pandas for Python
df['col1 & col2'] = df['col1']+df['col2']
#Output
#col1 col2 col1 & col2
#A1 A2 A1A2
#B1 B2 B1B2