dataframe[new_column_name] = column_values_list<\/em>. Here is the code to add age column to our dataframe. The age values of 4 students is stored in a list and assigned to the column.<\/p>\n\n\n\nage = [16,15,17,14]
df['age'] = age
print(df)
## output
Name ID age
0 John 1 16
1 Jane 2 15
2 Jim 3 17
3 Joe 4 14<\/pre>\n\n\n\nThe column values can be of different data type, it will still work. Here is an example, where some values are numbers while some are text. The following code will give the same output as above.<\/p>\n\n\n\n
age = [16,'15',17,'14']
df['age'] = age
print(df)<\/pre>\n\n\n\nPlease note, the number of column values should be same as the length of index column, otherwise it will give an error. Here is an example where we add 3 column values whereas our dataframe has 4 index values.<\/p>\n\n\n\n
age = [16,15,17]
df['age'] = age
print(df)
## output
ValueError: Length of values (3) does not match length of index (4)<\/pre>\n\n\n\nAlso, when we add a new column, it will modify the existing dataframe instead of creating its copy.<\/p>\n\n\n\n