Course Content

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data

Outputting Columns by Title Outputting Rows by Index Selecting Specific Rows and Columns Learning More About Indexation Getting Familiar With lambda Functions Expanding Functionality of the .iloc[] Attribute

2. Dealing With Conditions

Setting Condition Selecting Data Based on Condition Dealing With Several Conditions Making Your Code Beautiful Conditions Quiz

3. Extracting Data

Is Data in ...?Combining Your Knowledge Between Method Extracting Specific Data Finding the Smallest Values of a Column Finding the Largest Values of a Column Finding the Correlation

4. Aggregating Data

Getting Familiar With the .groupby() Method Grouping by Several Columns Complicated Grouping Advanced Grouping Dealing With Pivot Tables Creating a Pivot Table

5. Preprocessing Data

Checking for Missing Values Calculating the Number of Missing Values What Will We Do With the NaN Values?How to Delete Only NaN Values?Filling In the Missing Values Managing Categorical Variables Checking the Column Type Managing an Incorrect Column Renaming the Column

Is Data in ...?

In this section, we will continue extracting data using specific conditions. Here, you will become familiar with the helpful method called .isin(). But firstly, you need to examine the dataset. Look at the first five rows:


              123
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
print(data.head())

Now, take a look at the example and the explanation below:


              12345
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
data_extracted = data.loc[data['Manufacturer'].isin(models)]
print(data_extracted.head())

Explanation:

If you remember, we always put the conditions inside the .loc[] attribute. Here, we do the same. The .isin(list) method checks if the values from the column are in the array. In our case, we check if values from the column 'Manufacturer' are in the list models.

Task

Swipe to show code editor

Your task here is to extract data about cars where values from the column 'Color' are equal to 'Grey', 'White', 'Black'. Follow the algorithm to easily manage with the task:

Create the colors list with the elements 'Grey', 'White', 'Black' (in this order).
Extract values from the column 'Color' that the list color consists of. Use the .loc[] attribute.
Output the last five rows of the dataset data_extracted.

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 3. Chapter 1

Is Data in ...?


              123
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
print(data.head())

Now, take a look at the example and the explanation below:


              12345
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
data_extracted = data.loc[data['Manufacturer'].isin(models)]
print(data_extracted.head())

Explanation:

Task

Swipe to show code editor

Your task here is to extract data about cars where values from the column 'Color' are equal to 'Grey', 'White', 'Black'. Follow the algorithm to easily manage with the task:

Create the colors list with the elements 'Grey', 'White', 'Black' (in this order).
Extract values from the column 'Color' that the list color consists of. Use the .loc[] attribute.
Output the last five rows of the dataset data_extracted.

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 3. Chapter 1

Is Data in ...?


              123
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
print(data.head())

Now, take a look at the example and the explanation below:


              12345
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
data_extracted = data.loc[data['Manufacturer'].isin(models)]
print(data_extracted.head())

Explanation:

Task

Swipe to show code editor

Your task here is to extract data about cars where values from the column 'Color' are equal to 'Grey', 'White', 'Black'. Follow the algorithm to easily manage with the task:

Create the colors list with the elements 'Grey', 'White', 'Black' (in this order).
Extract values from the column 'Color' that the list color consists of. Use the .loc[] attribute.
Output the last five rows of the dataset data_extracted.

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

Everything was clear?

Thanks for your feedback!


              123
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
print(data.head())

Now, take a look at the example and the explanation below:


              12345
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
data_extracted = data.loc[data['Manufacturer'].isin(models)]
print(data_extracted.head())

Explanation:

Task

Swipe to show code editor

Your task here is to extract data about cars where values from the column 'Color' are equal to 'Grey', 'White', 'Black'. Follow the algorithm to easily manage with the task:

Create the colors list with the elements 'Grey', 'White', 'Black' (in this order).
Extract values from the column 'Color' that the list color consists of. Use the .loc[] attribute.
Output the last five rows of the dataset data_extracted.

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

Section 3. Chapter 1

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