count() to concatenate strings in Pandas.str methods

Pandas

Number of occurences of pattern in a string .
Returns Series or Index

Options

pattern ( required ) : Pattern to search in string
flag : (optional ) : we can use re module.

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex']}
df = pd.DataFrame(data=my_dict)
print(df.NAME.str.count(pat='a'))

Output

0    1
1    1
2    0

Here we have searched for a and returned number of occurences.

Let us display by adding a column.

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex']}
df = pd.DataFrame(data=my_dict)
df['number']=df.NAME.str.count(pat='a')
print(df)

Output

   NAME  number
0  Ravi       1
1  Raju       1
2  Alex       0

Flag

Let us match pattern with case insensitive.

import pandas as pd 
import re 
my_dict={'NAME':['Ravi','Raju','Alex']}
df = pd.DataFrame(data=my_dict)
df['number']=df.NAME.str.count('r', re.I)
print(df)

Output

   NAME  number
0  Ravi       1
1  Raju       1
2  Alex       0

In above code we have included re module and this is a case insensitive pattern matching.

Escaping characters

To search some characters need to be escaped.

import pandas as pd 
my_dict={'NAME':['Ravi$a','Raj$u$b','Alex']}
df = pd.DataFrame(data=my_dict)
df['number']=df.NAME.str.count(pat='\$')
print(df)

Output

      NAME  number
0   Ravi$a       1
1  Raj$u$b       2
2     Alex       0

Counting the total occurrence of sub-string in column

import pandas as pd 
df = pd.DataFrame(['John','Mac','Arnold','Krish','Roni'],
                  columns=['Names'])  
df.Names.str.count('r')

Output is here

We will use sum() to get total matching substrings.

df.Names.str.count('r').sum()

Output is

Pandas contains() Converting char case slice() split()

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str.count()

Options

Flag

Escaping characters

Counting the total occurrence of sub-string in column

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