pandas insert column in the beginning
insert_index = 0
insert_colname = 'new column'
insert_values = [1, 2, 3, 4, 5] # this can be a numpy array too
df.insert(loc=insert_index, column=insert_colname, value=insert_values)pandas insert column in the beginning
insert_index = 0
insert_colname = 'new column'
insert_values = [1, 2, 3, 4, 5] # this can be a numpy array too
df.insert(loc=insert_index, column=insert_colname, value=insert_values)how to add a column to a pandas df
#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 dataframehow to add the column to the beginning of dataframe
# Third position would be at index 2, because of zero-indexing.
df.insert(2, 'new-col', data)python how to add columns to a pandas dataframe
# 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 etchow to add new column to dataframe
# Import pandas package
import 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
dfhow to add a new column to the pandas df
import pandas as pd
data = {'Name': ['Josh', 'Stephen', 'Drake', 'Daniel'],
'Height': [5.5, 6.0, 5.3, 4.9]}
'''
printing data at this point will show the following
Name Height
0 Josh 5.1
1 Stephen 6.2
2 Drake 5.1
3 Daniel 5.2
'''
df.insert(2, "Age", [20, 21, 20, 19])
'''
printing data now will show the following
Name Height Age
0 Josh 5.1 20
1 Stephen 6.2 21
2 Drake 5.1 20
3 Daniel 5.2 19
'''Copyright © 2021 Codeinu
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