str.contains to search string or pattern matching in columns series using Pandas

Pandas

Searches for string or pattern matching with different options.
Returns boolean searies

We will read data from one excel file ( student.xlsx ) by using read_excel() to create a DataFrame.

import pandas as pd 
my_data = pd.read_excel('student.xlsx')
print(my_data)

This will return all the rows

We will use contains() to get only rows having Al in name column. We used the option case=False so this is a case insensitive matching. You can make it case sensitive by changing case option to case=True

import pandas as pd 
my_data = pd.read_excel('student.xlsx')
my_data=my_data[my_data['name'].str.contains('Al',case=False)]
print(my_data)

Output

    id       name class  mark     sex
5    6  Alex John  Four    55    male
10  11     Ronald   Six    89  female

Check this Exercise on how to use str.contains(), dataframe.max(), min() to analyse search queries and cliks

regex=True | False

We can use regual expression pattern matching by setting the option regex=True.
We will collect rows where name column is starting with A or B

import pandas as pd 
my_data = pd.read_excel('student.xlsx')
my_data=my_data[my_data['name'].str.contains('^[AB]',case=True,regex=True)]
print(my_data)

Name column ending with d

my_data=my_data[my_data['name'].str.contains('d$',regex=True)]

Name column ending with a or d

my_data=my_data[my_data['name'].str.contains('[ad]$',regex=True)]

Name column not having Al

my_data=my_data[my_data['name'].str.contains('^((?!Al).)*$',case=True,regex=True)]

my_data=my_data[~my_data['name'].str.contains('Al',case=False)]

str.contains.sum()

Pandas read_csv() read_excel() to_excel()

Numpy arrys Python & MySQL Python- Tutorials