Write a program in Python to filter City column elements by removing the unique prefix in a given dataframe

Assume you have a dataframe, the result for removing unique prefix city names are,

  Id  City 2 3 Kolkata 3 4 Hyderabad 6 7 Haryana 8 9 Kakinada 9 10 Kochin

To solve this, we will follow the steps given below −

Solution

• Define a dataframe

• Create an empty list to append all the city column values first char’s,

l = [] for x in df['City']:    l.append(x[0])

• Create another empty list to filter repeated char.

Set for loop and if condtion to append unique char’s. It is defined below,

l1 = [] for j in l:    if(l.count(j)>1):       if(j not in l1):          l1.append(j)

• Create another empty list. Set for loop to access city column values and check the elements first char is present in l1 then append it to another list.

l2 = [] for x in df['City']:    if(x[0] in l1):       l2.append(x)

• Finally, verify the l2 elements is present in the city column or not and print the dataframe using isin().

df[df['City'].isin(l2)]

Example

Let’s check the following code to get a better understanding −

import pandas as pd df = pd.DataFrame({'Id':[1,2,3,4,5,6,7,8,9,10],                      'City':['Chennai','Delhi','Kolkata','Hyderabad','Pune','Mumbai','Haryana','B engaluru','Kakinada','Kochin']                   }) l = [] for x in df['City']:    l.append(x[0]) l1 = [] for j in l:    if(l.count(j)>1):       if(j not in l1):          l1.append(j) l2 = [] for x in df['City']:    if(x[0] in l1):       l2.append(x) print(df[df['City'].isin(l2)])

Output

 Id   City 2 3 Kolkata 3 4 Hyderabad 6 7 Haryana 8 9 Kakinada 9 10 Kochin