# Stack the DataFrames on top of each other
#survey_sub and survey_sub_last10 are both dataframes
vertical_stack = pd.concat([survey_sub, survey_sub_last10], axis=0)
# Place the DataFrames side by side
horizontal_stack = pd.concat([survey_sub, survey_sub_last10], axis=1)
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
In [6]: result = pd.concat(frames, keys=['x', 'y', 'z'])
# Stack the DataFrames on top of each other
vertical_stack = pd.concat([survey_sub, survey_sub_last10], axis=0)
# Place the DataFrames side by side
horizontal_stack = pd.concat([survey_sub, survey_sub_last10], axis=1)
In [12]:
pd.concat([df,df1], axis=0, ignore_index=True)
Out[12]:
attr_1 attr_2 attr_3 id quantity
0 0 1 NaN 1 20
1 1 1 NaN 2 23
2 1 1 NaN 3 19
3 0 0 NaN 4 19
4 1 NaN 0 5 8
5 0 NaN 1 6 13
6 1 NaN 1 7 20
7 1 NaN 1 8 25
# import pandas library
import pandas as pd
# create pandas DataFrame
df = pd.DataFrame({'team': ['India', 'South Africa', 'New Zealand', 'England'],
'points': [10, 8, 3, 5],
'runrate': [0.5, 1.4, 2, -0.6],
'wins': [5, 4, 2, 2]})
# print the DataFrame
print(df)
# create a new DataFrame
df2 = pd.DataFrame([[1, 2], [2, 1], [3, 4], [0, 3]],
columns=['matches_left', 'lost'])
# concat and Print the new DataFrame
print(pd.concat([df, df2], axis=1))