When a part of any column in Dataframe is important and the need is to take it separate, we can split a column on the basis of the requirement.
We can use Pandas .str accessor, it does fast vectorized string operations for Series and Dataframes and returns a string object. Pandas str accessor has number of useful methods and one of them is str.split, it can be used with split to get the desired part of the string. To get the nth part of the string, first split the column by delimiter and apply str[n-1] again on the object returned, i.e. Dataframe.columnName.str.split(" ").str[n-1].
Let’s make it clear by examples.
Code #1: Print a data object of the splitted column.
import pandas as pdimport numpy as npdf = pd.DataFrame({'Geek_ID':['Geek1_id', 'Geek2_id', 'Geek3_id', 'Geek4_id', 'Geek5_id'], 'Geek_A': [1, 1, 3, 2, 4], 'Geek_B': [1, 2, 3, 4, 6], 'Geek_R': np.random.randn(5)}) # Geek_A Geek_B Geek_ID Geek_R# 0 1 1 Geek1_id random number# 1 1 2 Geek2_id random number# 2 3 3 Geek3_id random number# 3 2 4 Geek4_id random number# 4 4 6 Geek5_id random number print(df.Geek_ID.str.split('_').str[0]) |
0 Geek1 1 Geek2 2 Geek3 3 Geek4 4 Geek5 dtype: object
Code #2: Print a list of returned data object.
import pandas as pdimport numpy as npdf = pd.DataFrame({'Geek_ID':['Geek1_id', 'Geek2_id', 'Geek3_id', 'Geek4_id', 'Geek5_id'], 'Geek_A': [1, 1, 3, 2, 4], 'Geek_B': [1, 2, 3, 4, 6], 'Geek_R': np.random.randn(5)}) # Geek_A Geek_B Geek_ID Geek_R# 0 1 1 Geek1_id random number# 1 1 2 Geek2_id random number# 2 3 3 Geek3_id random number# 3 2 4 Geek4_id random number# 4 4 6 Geek5_id random number print(df.Geek_ID.str.split('_').str[0].tolist()) |
['Geek1', 'Geek2', 'Geek3', 'Geek4', 'Geek5']
Code #3: Print a list of elements.
import pandas as pdimport numpy as np df = pd.DataFrame({'Geek_ID':['Geek1_id', 'Geek2_id', 'Geek3_id', 'Geek4_id', 'Geek5_id'], 'Geek_A': [1, 1, 3, 2, 4], 'Geek_B': [1, 2, 3, 4, 6], 'Geek_R': np.random.randn(5)}) # Geek_A Geek_B Geek_ID Geek_R# 0 1 1 Geek1_id random number# 1 1 2 Geek2_id random number# 2 3 3 Geek3_id random number# 3 2 4 Geek4_id random number# 4 4 6 Geek5_id random number print(df.Geek_ID.str.split('_').str[1].tolist()) |
['id', 'id', 'id', 'id', 'id']
