Course Content

Data Manipulation using pandas

1. Preprocessing Data: Part I

What is Data Preprocessing?Types consistency Poor Data Presentation Manipulating Strings Challenge Replacing Specific Elements Simultaneous Replacement Challenge

2. Preprocessing Data: Part II

Logical Inconsistency Removing Rows Challenge Outliers Challenge Missing Values Filling NA values Challenge

3. Grouping Data

What is Grouping Data?Grouping in pandas [1/2]Challenge Grouping in pandas [2/2]Challenge Grouping by Several Columns Challenge

4. Aggregating and Visualizing Data

Advanced Aggregation [1/2]Challenge Advanced Aggregation [2/2]Challenge Histograms Challenge Bar and Scatter Plots Other Types of Graphs Challenge 1 Challenge 2

5. Joining Data

What is Joining Data?Left Join Right Join Inner Join Outer Join Concatenation

Challenge

Now it's your turn to remove rows with wrong data!

Task

Swipe to show code editor

Get indexes of rows having 'inconsistent' data. Follow the next steps:

Apply the .loc[] property to the df dataframe.
Set condition on rows: row sums of 2-14 columns ([2:15]) must be not equal to values in the 'hhsize' column.
Use the .index attribute.

Drop rows using indexes saved within ind variable. Set the inplace parameter to rewrite the changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 3

Challenge

Now it's your turn to remove rows with wrong data!

Task

Swipe to show code editor

Get indexes of rows having 'inconsistent' data. Follow the next steps:

Apply the .loc[] property to the df dataframe.
Set condition on rows: row sums of 2-14 columns ([2:15]) must be not equal to values in the 'hhsize' column.
Use the .index attribute.

Drop rows using indexes saved within ind variable. Set the inplace parameter to rewrite the changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 3

Challenge

Now it's your turn to remove rows with wrong data!

Task

Swipe to show code editor

Get indexes of rows having 'inconsistent' data. Follow the next steps:

Apply the .loc[] property to the df dataframe.
Set condition on rows: row sums of 2-14 columns ([2:15]) must be not equal to values in the 'hhsize' column.
Use the .index attribute.

Drop rows using indexes saved within ind variable. Set the inplace parameter to rewrite the changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Now it's your turn to remove rows with wrong data!

Task

Swipe to show code editor

Get indexes of rows having 'inconsistent' data. Follow the next steps:

Apply the .loc[] property to the df dataframe.
Set condition on rows: row sums of 2-14 columns ([2:15]) must be not equal to values in the 'hhsize' column.
Use the .index attribute.

Drop rows using indexes saved within ind variable. Set the inplace parameter to rewrite the changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 2. Chapter 3

Switch to desktop for real-world practiceContinue from where you are using one of the options below