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Pandas melt()The Pandas.melt() function is used to unpivot the DataFrame from a wide format to a long format. Its main task is to massage a DataFrame into a format where some columns are identifier variables and remaining columns are considered as measured variables, are unpivoted to the row axis. It leaves just two non-identifier columns, variable and value. Syntaxpandas.melt(frame, id_vars=None, value_vars=None, var_name=None, value_name='value', col_level=None) Parameters
ReturnsIt returns the unpivoted DataFrame as the output. Example
# importing pandas as pd
import pandas as pd
# creating a dataframe
info = pd.DataFrame({'Name': {0: 'Parker', 1: 'Smith', 2: 'John'},
'Language': {0: 'Python', 1: 'Java', 2: 'C++'},
'Age': {0: 22, 1: 30, 2: 26}})
# Name is id_vars and Course is value_vars
pd.melt(info, id_vars =['Name'], value_vars =['Language'])
info
Output Name Language Age 0 Parker Python 22 1 Smith Java 30 2 John C++ 26 Example2
import pandas as pd
info = pd.DataFrame({'A': {0: 'p', 1: 'q', 2: 'r'},
'B': {0: 40, 1: 55, 2: 25},
'C': {0: 56, 1: 62, 2: 42}})
pd.melt(info, id_vars=['A'], value_vars=['C'])
pd.melt(info, id_vars=['A'], value_vars=['B', 'C'])
pd.melt(info, id_vars=['A'], value_vars=['C'],
var_name='myVarname', value_name='myValname')
Output A myVarname myValname 0 p C 56 1 q C 62 2 r C 42
Next TopicDataFrame.merge()
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