Pandas is basically the library in Python used for Data Analysis and Manipulation. To add a new Column in the data frame we have a variety of methods. But here in this post, we are discussing adding a new column by using the dictionary.
Let’s take Example!
# Python program to illustrate # Add a new column in Pandas # Importing the pandas Library import pandas as pd # creating a data frame with some data values. data_frame = pd.DataFrame([[i] for i in range(7)], columns =['data']) print (data_frame) |
Output:
data 0 0 1 1 2 2 3 3 4 4 5 5 6 6
Now Using the above-written method lets try to add a new column to it. Let’s add the New columns named as “new_data_1”.
Map Function : Adding column “new_data_1” by giving the functionality of getting week name for the column named “data”. Call map and pass the dict, this will perform a lookup and return the associated value for that key.
Let’s Introduce variable week data typed as Dictionary that includes the name of days in the week.
# Python program to illustrate # Add a new column in Pandas # Data Frame Using a Dictionary import pandas as pd data_frame = pd.DataFrame([[i] for i in range(7)], columns =['data']) # Introducing weeks as dictionary weeks = {0:'Sunday', 1:'Monday', 2:'Tuesday', 3:'Wednesday', 4:'Thursday', 5:'Friday', 6:'Saturday'} # Mapping the dictionary keys to the data frame. data_frame['new_data_1'] = data_frame['data'].map(weeks) print (data_frame) |
Output:
data new_data_1 0 0 Sunday 1 1 Monday 2 2 Tuesday 3 3 Wednesday 4 4 Thursday 5 5 Friday 6 6 Saturday
And, we have successfully added a column (Sunday, Monday….) at the end.
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