Classwork 13

Pandas Fundamental IV: Missing Values; Duplicate Values

Author

Byeong-Hak Choe

Published

April 6, 2026

Modified

March 30, 2026

Direction

The netflix.csv file (with its pathname https://bcdanl.github.io/data/netflix.csv) contains a list of 6,000 titles that were available to watch in November 2019 on the video streaming service Netflix. It includes four variables: the video’s title, director, the date Netflix added it (date_added), and its type (category).

import pandas as pd 
import numpy as np

# Below is for an interactive display of DataFrame in Colab
from google.colab import data_table
data_table.enable_dataframe_formatter()

netflix = pd.read_csv(
    "https://bcdanl.github.io/data/netflix.csv"
)

Question 1

Identify all observations with a missing value in the director variable.

Answer:

Question 2

Identify all observations with a non-missing value in the date_added variable.

Answer:

Question 3

Count the number of missing values in the director variable.

Answer:

Question 4

Count the values in date_added, including missing values.

Answer:

Question 5

Drop all observations with a NaN value in the director variable.

Answer:

Question 6

Drop all observations with any missing value in the DataFrame.

Answer:

Question 7

Find the duplicated values in the title variable.

Answer:

Question 8

Keep only the first occurrence of each unique title.

Answer:

Question 9

Keep only the last occurrence of each unique title.

Answer:

Question 10

Remove all duplicated title values entirely, so that only titles appearing exactly once remain.

Answer:

Question 11

Identify the days when Netflix added only one title to its catalog.

Answer:

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