str.contains.sum or max or min to get values from dataframe in Pandas

import pandas as pd
my_dict={'NAME':['Ravi','Raju','Alex'],
         'ID':[1,2,3],
         'MATH':[80,40,70]
         }
df = pd.DataFrame(data=my_dict) # crate DataFrame
print(df.MATH.sum()) # 190
print(df.MATH.max()) # 80
print(df.MATH.min()) # 40

print(df.MATH.mean()) # 63.33
print(df.MATH.mode()) # 
print(df.MATH.median()) # 70.0

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.

sum of all marks of 4^th class.

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=my_data[my_data.my_class.str.contains('Four')]
print(my_data.mark.sum())

Output is

Maximum mark of 3^rd class

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=my_data[my_data.my_class.str.contains('Three')]
print(my_data.mark.max())

Output is

Maximum mark is 85 but who is the student got the highest mark ?

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=my_data[my_data.my_class.str.contains('Three')]
print(my_data.mark.max())
print(my_data[my_data.mark == my_data.mark.max()])

Output

85
   ID      name my_class  mark   sex
1   2  Max Ruin    Three    85  male

Let us try getting lowest ( Minimum ) value of mark in class

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=my_data[my_data.my_class.str.contains('Three')]
print(my_data.mark.min())

Output

The matching row or get the row with lowest mark.

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=my_data[my_data.my_class.str.contains('Three')]
print(my_data.mark.min())
print(my_data[my_data.mark == my_data.mark.min()])

Output

55
   ID    name my_class  mark   sex
2   3  Arnold    Three    55  male

Mean value of marks of class three

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=my_data[my_data.my_class.str.contains('Three')]
print(my_data.mark.mean())

Similarly we can find out other values .

print(my_data.mark.median())
print(my_data.mark.mode())

idxmax()

We can get id of the row with maximum value ( not the maximum value itself )

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=pd.DataFrame(my_data)
print(my_data.mark.idxmax())
print(my_data[my_data.ID == my_data.mark.idxmax()])

Output

32
    ID       name my_class  mark     sex
31  32  Binn Rott    Seven    90  female

idxmin()

We can get id of the row with minimum value

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=pd.DataFrame(my_data)
print(my_data.mark.idxmin())
print(my_data[my_data.ID == my_data.mark.idxmin()])

Output

18
    ID   name my_class  mark   sex
17  18  Honny     Five    75  male

count()

Counting number of records

import pandas as pd 
my_data=pd.read_excel("student.xlsx")
my_data=my_data[my_data.my_class.str.contains('Three')]
print(my_data.mark.count())

Output

str.contains

Pandas read_csv() read_excel() to_excel()

Numpy arrays Python & MySQL Python- Tutorials

Subscribe to our YouTube Channel here

str.contains.sum(): sum, maximum, mininum values

idxmax()

idxmin()

count()

Subscribe