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Adding new column to existing DataFrame in Pandas

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

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

Source: pythonexamples.org

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)

Source: itsmycode.com

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)

Source: itsmycode.com

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)

Source: itsmycode.com

Add dataframe column to set

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

-1

Source: stackoverflow.com

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