Add a new column in Pandas Data Frame Using a Dictionary
Last Updated :
09 Nov, 2018
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!
import pandas as pd
data_frame = pd.DataFrame([[i] for i in range ( 7 )], columns = [ 'data' ])
print (data_frame)
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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.
import pandas as pd
data_frame = pd.DataFrame([[i] for i in range ( 7 )], columns = [ 'data' ])
weeks = { 0 : 'Sunday' , 1 : 'Monday' , 2 : 'Tuesday' , 3 : 'Wednesday' ,
4 : 'Thursday' , 5 : 'Friday' , 6 : 'Saturday' }
data_frame[ 'new_data_1' ] = data_frame[ 'data' ]. map (weeks)
print (data_frame)
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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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