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