Find Missing Values in a Data Set

The function to fill in NAN values with 100,if df is the dataframe object

• fillna(100)

• df.fillna(100)

• df.fillna(0)

• df.fill(100)

Function to drop the rows with NAN values

• df.drop()

• df.dropna()

• df.delete

• df.deletena()

Missing values are the values that carry no computational significance.

• False

• True

............... can be used to detect missing values for a dataframe object df.

• df.null()

• df.isnull()

• df.isempty()

• df.nonnull()

Which among the following is correct to filter values from a series object S having values less than 50?

• S[S less than 50]

• S[S < 50]

• [S < 50]

• S ( S <50)

Which function will drop rows that have all NaN values?

• dropna(how="all")

• dropna()

• dropna(axis=1)

Which function will copy the value from the above adjacent cell?

• fillna()

• fillna(method="ffill")

• fillna(dictionary object)