PYTHON

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 dataframe

Adding new column to existing DataFrame in Pandas by assigning a list

# 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)

# declare a new list and add the values into the list
match_lost = [2, 1, 3, 4]

# assign the list to the new DataFrame Column
df["lost"] = match_lost

# Print the new DataFrame
print(df)

pandas dataframe add column from another column

import pandas as pd

df = pd.DataFrame({'a':[1,2], 'b':[3,4]})
df['c'] = df.apply(lambda row: row.a + row.b, axis=1)
df
#    a  b  c
# 0  1  3  4
# 1  2  4  6

how to add column to the Dataframe in python

#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

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 etc 

Adding new column to existing DataFrame in Pandas using assign 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)

# append multiple columns to Pandas DataFrame
df2 = df.assign(lost=[2, 1, 3, 4], matches_remaining=[2, 3, 1, 1])

# Print the new DataFrame
print(df2)

insert new column to dataframe

group = np.random.randint(10, size=6)
df_new['Group'] = group

add dataframe column to set

In [79]:

df
Out[79]:
         Date, Open, High,  Low,  Close
0  01-01-2015,  565,  600,  400,    450
In [80]:

df['Name'] = 'abc'
df
Out[80]:
         Date, Open, High,  Low,  Close Name
0  01-01-2015,  565,  600,  400,    450  abc

Add new column of dataframe

Other['Extracurr'] = count

Adding new column to existing DataFrame in Pandas

# 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
print(df)

Adding new column to existing DataFrame in Pandas

# 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)


# insert the new column at the specific position
df.insert(3, "lost", [2, 1, 3, 4], True)

# Print the new DataFrame
print(df)

add new column to pandas 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
df

add dataframe column to set

set_id = set(df["Id"])
print(set_id)
{'1-wYH2LEcmk', '08QMXEQbEWw', '0pPU8CtwXTo', '0ANuuVrIWJw', '-KkJz3CoJNM'}