Course Content
Pandas First Steps
Pandas First Steps
2. Reading Files in Pandas
3. Analyzing the Data
Viewing the DataQuiz: Using HeadQuiz: Head, Tail, and SampleExploring the DatasetColumn Names and Data TypesFinding Null ValuesQuiz: Identifying Null ValuesChallenge: Dropping Null ValuesChallenge: Filling Null ValuesQuiz: Null ValuesDescribing the Datamax() and min()Quiz: Statistical Operationssum() and count()Unique Values
Challenge: Dropping Null Values
If the dataset has rows with null values, we should consider removing them. In pandas, this can be achieved using the dropna() method.
Task
Swipe to start coding
- Find the length of
wine_databefore removing null values and assign the result to thelength_beforevariable. - Remove rows with null values.
- Find the length of
wine_dataafter removing null values and assign the result to thelength_aftervariable. - Print the number of removed rows based on the
length_beforeandlength_aftervariables.
Solution
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Section 3. Chapter 8
Challenge: Dropping Null Values
If the dataset has rows with null values, we should consider removing them. In pandas, this can be achieved using the dropna() method.
Task
Swipe to start coding
- Find the length of
wine_databefore removing null values and assign the result to thelength_beforevariable. - Remove rows with null values.
- Find the length of
wine_dataafter removing null values and assign the result to thelength_aftervariable. - Print the number of removed rows based on the
length_beforeandlength_aftervariables.
Solution
Switch to desktop for real-world practiceContinue from where you are using one of the options belowEverything was clear?
Thanks for your feedback!
Section 3. Chapter 8
Switch to desktop for real-world practiceContinue from where you are using one of the options below