#using the insert function:
df.insert(location, column_name, list_of_values)#example
df.insert(0,'new_column',['a','b','c'])#explanation:#put "new_column" as first column of the dataframe#and puts 'a','b' and 'c' as values#using array-like access:
df['new_column_name']= value
#df stands for dataframe
#using the insert function:
df.insert(location, column_name, list_of_values)#example
df.insert(0,'new_column',['a','b','c'])#explanation:#put "new_column" as first column of the dataframe#and puts 'a','b' and 'c' as values#using array access:
df['new_column_name']= value
# Basic syntax:
pandas_dataframe['new_column_name']=['list','of','column','values']# Note, the list of column values must have length equal to the number# of rows in the pandas dataframe you are adding it to.# Add column in which all rows will be value:
pandas_dataframe['new_column_name']= value
# Where value can be a string, an int, a float, and etc
In [79]:
df
Out[79]:
Date, Open, High, Low, Close
001-01-2015,565,600,400,450
In [80]:
df['Name']='abc'
df
Out[80]:
Date, Open, High, Low, Close Name
001-01-2015,565,600,400,450 abc
# Import pandas packageimport pandas as pd
# Define a dictionary containing Students data
data ={'Name':['Jai','Princi','Gaurav','Anuj'],'Height':[5.1,6.2,5.1,5.2],'Qualification':['Msc','MA','Msc','Msc']}# Convert the dictionary into DataFrame
df = pd.DataFrame(data)# Declare a list that is to be converted into a column
address =['Delhi','Bangalore','Chennai','Patna']# Using 'Address' as the column name# and equating it to the list
df['Address']= address
# Observe the result
df