Python | Pandas Series.str.strip(), lstrip() and rstrip()

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages that makes importing and analyzing data much easier.
Pandas provide 3 methods to handle white spaces(including New lines) in any text data. As can be seen in the name, str.lstrip() is used to remove spaces from the left side of the string, str.rstrip() to remove spaces from the right side of the string, and str.strip() remove spaces from both sides. Since these are pandas functions with the same name as Python’s default functions, .str has to be prefixed to tell the compiler that a Pandas function is being called.

Syntax:
Series.str.strip()

Return Type: Series with removed spaces

Dataset

In the following examples, the data frame used contains data from some NBA players. To download the CSV used in the code, click here. Since none of the values in the data frame has any extra spaces, the spaces are added in some elements using str.replace() method. Let’s load the dataset.

Python3

# importing pandas module
import pandas as pd

# reading csv file from url
data = pd.read_csv("nba.csv")

print(data.head())

Output:

            Name            Team  Number Position   Age Height  Weight            College     Salary
0  Avery Bradley  Boston Celtics     0.0       PG  25.0    6-2   180.0              Texas  7730337.0  
1    Jae Crowder  Boston Celtics    99.0       SF  25.0    6-6   235.0          Marquette  6796117.0 
2   John Holland  Boston Celtics    30.0       SG  27.0    6-5   205.0  Boston University        NaN   
3    R.J. Hunter  Boston Celtics    28.0       SG  22.0    6-5   185.0      Georgia State  1148640.0 
4  Jonas Jerebko  Boston Celtics     8.0       PF  29.0   6-10   231.0                NaN  5000000.0 

Example 1:Using lstrip()

In this example, a new series similar to Team column is created which has 2 spaces in both start and end of string. After that, str.lstrip() method is applied and checked against a custom string with removed left side spaces.

Python3

# replacing team name and adding spaces in start and end
new = data["Team"].replace("Boston Celtics", " Boston Celtics ").copy()

# checking with custom removed space string
new.str.lstrip()=="Boston Celtics "

Output:
As shown in the output, the comparison is true after removing the left side spaces.

0       True
1       True
2       True
3       True
4       True
       ...  
453    False
454    False
455    False
456    False
457    False
Name: Team, Length: 458, dtype: bool

Example 2: Using strip()

In this example, str.strip() method is used to remove spaces from both left and right side of the string. A new copy of Team column is created with 2 blank spaces in both start and the end. Then str.strip() method is called on that series. After that, it is compared with ” Boston Celtics “, ” Boston Celtics” and “Boston Celtics ” to check if the spaces were removed from both sides or not.

Python3

# importing pandas module
import pandas as pd

# making data frame
data = pd.read_csv("https://media.geeksforgeeks.org/wp-content/uploads/nba.csv")

# replacing team name and adding spaces in start and end
new = data["Team"].replace("Boston Celtics", " Boston Celtics ").copy()

# checking with custom string
new.str.strip()==" Boston Celtic"
new.str.strip()=="Boston Celtics "
new.str.strip()==" Boston Celtic "

Output:
As shown in the output, the comparison is returning False for all 3 conditions, which means the spaces were successfully removed from both sides and the string is no longer having spaces.

0      False
1      False
2      False
3      False
4      False
       ...  
453    False
454    False
455    False
456    False
457    False
Name: Team, Length: 458, dtype: bool

Example 3: Using rstrip()

In this example, a new series similar to Team column is created which has 2 spaces in both start and end of string. After that str.rstrip() method is applied and checked against a custom string with removed right side spaces.

Python3

# importing pandas module
import pandas as pd

# making data frame
data = pd.read_csv("https://media.geeksforgeeks.org/wp-content/uploads/nba.csv")

# replacing team name and adding spaces in start and end
new = data["Team"].replace("Boston Celtics", " Boston Celtics ").copy()

# checking with custom removed space string
new.str.rstrip()==" Boston Celtics"

Output:
As shown in the output, the comparison is true after removing the right side spaces.

0       True
1       True
2       True
3       True
4       True
       ...  
453    False
454    False
455    False
456    False
457    False
Name: Team, Length: 458, dtype: bool