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concatenate dataframes
# 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)
concat dataframes
result = pd.concat([df1, df2])
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
how to concat on the basis of particular columns in pandas
In [6]: result = pd.concat(frames, keys=['x', 'y', 'z'])
How to Concatenate Dataframe in python
# 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)
pandas concat
pd.concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False,
keys=None, levels=None, names=None, verify_integrity=False)
result = pd.concat([df1, df4], axis=1)
result = pd.concat(frames, keys=['x', 'y', 'z'])
result = pd.concat([df1, df4], axis=1, join='inner')
result = pd.concat([df1, df4], axis=1, join_axes=[df1.index])
concat dataframe pandas
# provide list of dataframes
res = pd.concat([df1, df2])
Adding new column to existing DataFrame in Pandas using concat method
# 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))
dataframe concatenate
# Pandas for Python
df['col1 & col2'] = df['col1']+df['col2']
#Output
#col1 col2 col1 & col2
#A1 A2 A1A2
#B1 B2 B1B2
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