This is Jeopardy!: calculate miss in this course

In this course, I downloaded CSV file and manipulated DataFrame as instructed. But when i implemented third step, i could find out there’s something weird.
The description said, Note that in this example, we found 152 rows by filtering the entire dataset. But the result i got is 49 rows only. My code is below:

import pandas as pd

pd.set_option('display.max_colwidth', -1)
df = pd.read_csv('jeopardy.csv')

    ' Air Date': 'Air Date',
    ' Round': 'Round',
    ' Category': 'Category',
    ' Value': 'Value',
    ' Question': 'Question',
    ' Answer': 'Answer'
}, inplace=True)

def filter_strings(word_list):
    filtered_df = df[ df.apply(lambda row: all([word in row['Question'] for word in word_list]), axis=1) ]
    return filtered_df

filtered_df = filter_strings(['King', 'England'])
print('filtered_df.index: ' + str(len(filtered_df.index)))  # filterd_df.index: 49

Plz check out is there any missed data in leopardy.csv or any mistake in my code. :slight_smile:


I also get 49 rows when I run my code this way. If you use word.lower(), you get 152 rows.


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