Filtering pandas dataframe with multiple Boolean columns

Question

I am trying to filter a df using several Boolean variables that are a part of the df, but have been unable to do so.

Sample data:

A | B | C | D
John         


        

Answer 1

So, the easiest way to do this:

students = [ ('jack1', 'Apples1' , 341) ,
             ('Riti1', 'Mangos1'  , 311) ,
             ('Aadi1', 'Grapes1' , 301) ,
             ('Sonia1', 'Apples1', 321) ,
             ('Lucy1', 'Mangos1'  , 331) ,
             ('Mike1', 'Apples1' , 351),
              ('Mik', 'Apples1' , np.nan)
              ]
#Create a DataFrame object
df = pd.DataFrame(students, columns = ['Name1' , 'Product1', 'Sale1']) 
print(df)


    Name1 Product1  Sale1
0   jack1  Apples1    341
1   Riti1  Mangos1    311
2   Aadi1  Grapes1    301
3  Sonia1  Apples1    321
4   Lucy1  Mangos1    331
5   Mike1  Apples1    351
6     Mik  Apples1    NaN

# Select rows in above DataFrame for which ‘Product’ column contains the value ‘Apples’,
subset = df[df['Product1'] == 'Apples1']
print(subset)

 Name1 Product1  Sale1
0   jack1  Apples1    341
3  Sonia1  Apples1    321
5   Mike1  Apples1    351
6     Mik  Apples1    NA

# Select rows in above DataFrame for which ‘Product’ column contains the value ‘Apples’, AND notnull value in Sale

subsetx= df[(df['Product1'] == "Apples1")  & (df['Sale1'].notnull())]
print(subsetx)
    Name1   Product1    Sale1
0   jack1   Apples1      341
3   Sonia1  Apples1      321
5   Mike1   Apples1      351

# Select rows in above DataFrame for which ‘Product’ column contains the value ‘Apples’, AND Sale = 351

subsetx= df[(df['Product1'] == "Apples1")  & (df['Sale1'] == 351)]
print(subsetx)

   Name1 Product1  Sale1
5  Mike1  Apples1    351

# Another example
subsetData = df[df['Product1'].isin(['Mangos1', 'Grapes1']) ]
print(subsetData)

Name1 Product1  Sale1
1  Riti1  Mangos1    311
2  Aadi1  Grapes1    301
4  Lucy1  Mangos1    331

Here is the source of this code: https://thispointer.com/python-pandas-select-rows-in-dataframe-by-conditions-on-multiple-columns/
I added minor changes to it.