Course Content

Preprocessing Data

1. Data Exploration

Data Extracting Explore the Dataset Data Types

2. Data Cleaning

Missing and Wrong Data Work with NaNs Replace Numerical Missing Data with Values Dealing with Missing Ages Replace Categorical Missing Data with Values Replace Missing Values with Interpolation Removing Duplicates Removing Outliers Visualizing Outliers

3. Data Validation

Types Conversion Data Binning

4. Normalization & Standardization

Data Normalization Data Standardization

5. Data Encoding

Label Encoding One Hot Encoding

Removing Duplicates

To remove the duplicate rows, simply use function drop_duplicates(). To change the current dataframe, add inplace=True.


              123
            
new_data = data.drop_duplicates() # data is not modified
# or
data.drop_duplicates(inplace=True) # data is modified

Task

The planets dataset is given to you. Remove the duplicates and then check the new shape of dataframe. Compare it with the original shape.

Note that dataframe may have only distinct records, in this case, the shape will remain the same.

Task

The planets dataset is given to you. Remove the duplicates and then check the new shape of dataframe. Compare it with the original shape.

Note that dataframe may have only distinct records, in this case, the shape will remain the same.

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

Everything was clear?

Section 2. Chapter 7

Removing Duplicates

To remove the duplicate rows, simply use function drop_duplicates(). To change the current dataframe, add inplace=True.


              123
            
new_data = data.drop_duplicates() # data is not modified
# or
data.drop_duplicates(inplace=True) # data is modified

Task

The planets dataset is given to you. Remove the duplicates and then check the new shape of dataframe. Compare it with the original shape.

Note that dataframe may have only distinct records, in this case, the shape will remain the same.

Task

The planets dataset is given to you. Remove the duplicates and then check the new shape of dataframe. Compare it with the original shape.

Note that dataframe may have only distinct records, in this case, the shape will remain the same.

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

Everything was clear?

Section 2. Chapter 7

Removing Duplicates

To remove the duplicate rows, simply use function drop_duplicates(). To change the current dataframe, add inplace=True.


              123
            
new_data = data.drop_duplicates() # data is not modified
# or
data.drop_duplicates(inplace=True) # data is modified

Task

The planets dataset is given to you. Remove the duplicates and then check the new shape of dataframe. Compare it with the original shape.

Note that dataframe may have only distinct records, in this case, the shape will remain the same.

Task

The planets dataset is given to you. Remove the duplicates and then check the new shape of dataframe. Compare it with the original shape.

Note that dataframe may have only distinct records, in this case, the shape will remain the same.

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

Everything was clear?

To remove the duplicate rows, simply use function drop_duplicates(). To change the current dataframe, add inplace=True.


              123
            
new_data = data.drop_duplicates() # data is not modified
# or
data.drop_duplicates(inplace=True) # data is modified

Task

The planets dataset is given to you. Remove the duplicates and then check the new shape of dataframe. Compare it with the original shape.

Note that dataframe may have only distinct records, in this case, the shape will remain the same.

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

Section 2. Chapter 7

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