Blogs - Page 51 Of 116

Python Pandas program to replace all the NaN values with a scaler in a column of a Dataframe

In this python pandas program, we will replace all the NaN values with a scaler in a column using the pandas library.

Steps to solve the program

Import pandas library as pd.
Import NumPy library as np.
Create a dataframe using pd.DataFrame().
Replace all the NaN values with a scaler in a column of a Dataframe using df.fillna(value = 25,inplace = True).
Print the output.

				
					import pandas as pd
import numpy as np
d = {'Sr.no.':[1,2,3,4],'Name':['Alex','John','Peter','Klaus'],'Age':[30,np.nan,29,np.nan]}
df = pd.DataFrame(d)
print(df)
df.fillna(value = 25,inplace = True)
print("After filling nan values: \n",df)

Output :

				
					0   Sr.no.   Name   Age
0       1   Alex  30.0
1       2   John   NaN
2       3  Peter  29.0
3       4  Klaus   NaN
After filling nan values: 
    Sr.no.   Name   Age
0       1   Alex  30.0
1       2   John  25.0
2       3  Peter  29.0
3       4  Klaus  25.0

count Country wise population from a given data set

count the NaN values in a Dataframe

Python Pandas program to count Country wise population from a given dataset

In this python pandas program, we will count Country wise population from a given dataset using the pandas library.

Link for Dataset- https://www.kaggle.com/datasets/tanuprabhu/population-by-country-2020?resource=download

Steps to solve the program

Import pandas library as pd.
First, read the dataset using pd.read_csv().
Now drop the unnecessary columns from the dataset using df.drop().
Print the first 10 countries using df.head(10).

				
					import pandas as pd
df = pd.read_csv("population_by_country_2020.csv")
df1 = df.drop(['Yearly Change','Net Change','Density (P/Km²)','Land Area (Km²)',
              'Migrants (net)','Fert. Rate','Med. Age','Urban Pop %','World Share'],axis=1)
print(df1.head(10))

Output :

				
					0  Country (or dependency)  Population (2020)
0                   China         1440297825
1                   India         1382345085
2           United States          331341050
3               Indonesia          274021604
4                Pakistan          221612785
5                  Brazil          212821986
6                 Nigeria          206984347
7              Bangladesh          164972348
8                  Russia          145945524
9                  Mexico          129166028

write a DataFrame to a CSV file using a tab separato

replace all the NaN values with a scaler in a column of a Dataframe

Program to write a DataFrame to a CSV file

In this python pandas program, we will write a DataFrame to a CSV file using the pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Write the dataFrame to a CSV file using a tab separator using df.to_csv(‘new_file.csv’, sep=’\t’, index=False)
Print the output.

				
					import pandas as pd
d = {'Sr.no.':[1,2,3,4],'Name':['Alex','John','Peter','Klaus'],'Age':[30,27,29,33],'Salary':[50000,65000,58000,66000]}
df = pd.DataFrame(d)
df.to_csv('new_file.csv', sep='\t', index=False)
new = pd.read_csv('new_file.csv')
print(new)

Output :

				
					0  Sr.no.\tName\tAge\tSalary
0        1\tAlex\t30\t50000
1        2\tJohn\t27\t65000
2       3\tPeter\t29\t58000
3       4\tKlaus\t33\t66000

change the order of columns in a DataFrame

count Country wise population from a given data set

Python Pandas program to change the order of columns in a DataFrame

In this python pandas program, we will change the order of columns in a DataFrame using the pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Change the order of columns in a DataFrame using df[[‘Sr.no.’,’Name’,’Salary’,’Age’]].
Print the output.

				
					import pandas as pd
d = {'Sr.no.':[1,2,3,4],'Name':['Alex','John','Peter','Klaus'],'Age':[30,27,29,33],'Salary':[50000,65000,58000,66000]}
df = pd.DataFrame(d)
print("Original Dataframe: \n",df)
df = df[['Sr.no.','Name','Salary','Age']]
print('After re-ordering columns: \n',df)

Output :

				
					Original Dataframe: 
    Sr.no.   Name  Age  Salary
0       1   Alex   30   50000
1       2   John   27   65000
2       3  Peter   29   58000
3       4  Klaus   33   66000
After re-ordering columns: 
    Sr.no.   Name  Salary  Age
0       1   Alex   50000   30
1       2   John   65000   27
2       3  Peter   58000   29
3       4  Klaus   66000   33

rename columns of a given DataFrame

write a DataFrame to a CSV file using a tab separator

Python Pandas program to rename columns of a given DataFrame

In this python pandas program, we will rename columns of a given DataFrame using the pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Rename columns of a given DataFrame to A,B,C using df.rename(columns= {‘C1′:’A’,’C2′:’B’,’C3′:’C’}).
Print the output.

				
					import pandas as pd
d = {'C1':[1,3,8],'C2':[6,8,0],'C3':[8,2,6]}
df = pd.DataFrame(d)
print("Old Dataframe: \n",df)
df = df.rename(columns= {'C1':'A','C2':'B','C3':'C'})
print("New DataFrame after renaming columns:")
print(df)

Output :

				
					Old Dataframe: 
    C1  C2  C3
0   1   6   8
1   3   8   2
2   8   0   6
New DataFrame after renaming columns:
   A  B  C
0  1  6  8
1  3  8  2
2  8  0  6

get a list of column headers from the DataFrame

change the order of columns in a DataFrame

Python Pandas program to get a list of column headers from the DataFrame

In this python pandas program, we will get a list of column headers from the DataFrame using the pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Get a list of column headers from the DataFrame using list(df.columns.values).
Print the output.

				
					import pandas as pd
d = {'name':['Virat','Messi','Kobe'],'sport':['cricket','football','basketball']}
df = pd.DataFrame(d)
print("Dataframe: \n",df)
print("Names of columns: ")
print(list(df.columns.values))

Output :

				
					Dataframe: 
     name       sport
0  Virat     cricket
1  Messi    football
2   Kobe  basketball
Names of columns: 
['name', 'sport']

iterate over rows in a DataFrame

rename columns of a given DataFrame

Python Pandas program to iterate over rows in a DataFrame

In this python pandas program, we will iterate over rows in a DataFrame using pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Iterate over rows in a DataFrame using for loop and df.iterrows().
Print the records for each column using row[column1],row[columns2],……,row[column_n].

				
					import pandas as pd
import numpy as np
d = [{'name':'Yash','percentage':78},{'name':'Rakesh','percentage':80},{'name':'Suresh','percentage':60}]
df = pd.DataFrame(d)
for index, row in df.iterrows():
    print(row['name'], row['percentage'])

Output :

				
					Yash 78
Rakesh 80
Suresh 60

add a new column in a DataFrame

get a list of column headers from the DataFrame

Python Pandas program to add a new column in a DataFrame

In this python pandas program, we will add a new column in a DataFrame using pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Create a list of records for the new Salary column.
Add a Salary column in the given dataframe using df[‘Salary’] = Salary.
Print the output.

				
					import pandas as pd
d = {'Sr.no.':[1,2,3,4],'Name':['Alex','John','Peter','Klaus'],'Age':[30,27,29,33]}
df = pd.DataFrame(d)
print("Old Series: \n",df)
Salary = [50000,65000,58000,66000]
df['Salary'] = Salary
print("New Series: \n",df)

Output :

				
					Old Series: 
    Sr.no.   Name  Age
0       1   Alex   30
1       2   John   27
2       3  Peter   29
3       4  Klaus   33
New Series: 
    Sr.no.   Name  Age  Salary
0       1   Alex   30   50000
1       2   John   27   65000
2       3  Peter   29   58000
3       4  Klaus   33   66000

delete the record in a DataFrame

iterate over rows in a DataFrame

Python Pandas program to delete records from the DataFrame

In this python pandas program, we will delete records from the DataFrame using pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Delete records for John using df[df.Name != ‘John’].
It retains all records in the dataframe except for John.
Print the output.

				
					import pandas as pd
d = {'Sr.no.':[1,2,3,4],'Name':['Alex','John','Peter','Klaus'],'Age':[30,27,29,33]}
df = pd.DataFrame(d)
print("Old Series",df)
df = df[df.Name != 'John']
print("New Series")
print(df)

Output :

				
					Old Series    Sr.no.   Name  Age
0       1   Alex   30
1       2   John   27
2       3  Peter   29
3       4  Klaus   33
New DataFrame
   Sr.no.   Name  Age
0       1   Alex   30
2       3  Peter   29
3       4  Klaus   33

replace the value in a row

add a new column in a DataFrame

Python Pandas program to replace a DataFrame value

In this python pandas program, we will replace a DataFrame value using pandas library.

Steps to solve the program

Import pandas library as pd.
Create a dataframe using pd.DataFrame().
Replace John with Jim in the DataFrame using df[‘Name’].replace(‘John’,’Jim’).
Print the output.

				
					import pandas as pd
d = {'Sr.no.':[1,2,3,4],'Name':['Alex','John','Peter','Klaus'],'Age':[30,27,29,33]}
df = pd.DataFrame(d)
print(df)
print("Change the age of John to Jim:")
df['Name'] = df['Name'].replace('John','Jim')
print(df)

Output :

				
					0   Sr.no.   Name  Age
0       1   Alex   30
1       2   John   27
2       3  Peter   29
3       4  Klaus   33
Change the age of John to Jim:
   Sr.no.   Name  Age
0       1   Alex   30
1       2    Jim   27
2       3  Peter   29
3       4  Klaus   33

sort the DataFrame by ‘age’ column in ascending order

delete a record from the DataFrame