#The default is ascending
newdf = df.sort_values(["column1","column2"])

#Ascending to descend=Add False
newdf = df.sort_values(["column1","column2"], ascending = [True, False])

#Case where missing value is filled with 0
newdf = df.fillna(0)

#Aggregation method for each column of missing values
df.isnull().sum()

#Extract only missing row
df[df.isnull() == True]

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