drop rows with condition pandas

# Filter all rows for which the player's 
# age is greater than or equal to 25 
df_filtered = df[df['Age'] >= 25] 
  
# Print the new dataframe 
print(df_filtered.head(15) 
  
# Print the shape of the dataframe 
print(df_filtered.shape) 

# importing pandas as pd 
import pandas as pd 
  
# Read the csv file and construct the  
# dataframe 
df = pd.read_csv('nba.csv') 
  
# First filter out those rows which 
# does not contain any data 
df = df.dropna(how = 'all') 
  
# Filter all rows for which the player's 
# age is greater than or equal to 25 
df.drop(df[df['Age'] < 25].index, inplace = True) 
  
# Print the modified dataframe 
print(df.head(15)) 
  
# Print the shape of the dataframe 
print(df.shape) 

# import pandas library 
import pandas as pd 
  
# dictionary with list object in values 
details = { 
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 
              'Shivangi', 'Priya', 'Swapnil'], 
    'Age' : [23, 21, 22, 21, 24, 25], 
    'University' : ['BHU', 'JNU', 'DU', 'BHU',  
                    'Geu', 'Geu'], 
} 
  
# creating a Dataframe object  
df = pd.DataFrame(details, columns = ['Name', 'Age', 
                                      'University'], 
                  index = ['a', 'b', 'c', 'd', 'e', 'f']) 
  
# get names of indexes for which 
# column Age has value >= 21 
# and column University is BHU 
index_names = df[ (df['Age'] >= 21) & (df['University'] == 'BHU')].index 
  
# drop these given row 
# indexes from dataFrame 
df.drop(index_names, inplace = True) 
  
df