Conteúdo do Curso

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

Dealing With Several Conditions

Sometimes we need several conditions to be applied. For instance, we want to extract data on hazardous asteroids with a small minimum diameter. But how do we write two conditions simultaneously? Look at the table:

The example was included to help you deal with this topic. This code extracts data on large and hazardous asteroids, where the minimum estimated diameter is larger than 3.5 kilometers and 'hazardous' is True.


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] > 3.5) & (data['hazardous'] == True)]
print(data_extracted)

In the output, you can see all the rows that satisfy these two conditions:

est_diameter_min > 3.5;
hazardous == True.

Look at the following example with the or statement. This code will extract data on extremely small or large asteroids with a minimum estimated diameter less than 0.0005 kilometers and a maximum estimated diameter larger than 20 kilometers:


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] < 0.0005) | (data['est_diameter_max'] > 20)]
print(data_extracted)

In the output, you can see all the rows that satisfy one of these two conditions:

est_diameter_min < 0.0005;
est_diameter_max > 20.

Tarefa

Your task here is to extract data on very bright and not hazardous asteroids. The code should satisfy two conditions:

'absolute_magnitude' is larger than or equal to 25;
'hazardous' is False.

After this, output the random 5 rows of the data_extracted.

Tarefa

Your task here is to extract data on very bright and not hazardous asteroids. The code should satisfy two conditions:

'absolute_magnitude' is larger than or equal to 25;
'hazardous' is False.

After this, output the random 5 rows of the data_extracted.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 2. Capítulo 3

Dealing With Several Conditions


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] > 3.5) & (data['hazardous'] == True)]
print(data_extracted)

In the output, you can see all the rows that satisfy these two conditions:

est_diameter_min > 3.5;
hazardous == True.


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] < 0.0005) | (data['est_diameter_max'] > 20)]
print(data_extracted)

In the output, you can see all the rows that satisfy one of these two conditions:

est_diameter_min < 0.0005;
est_diameter_max > 20.

Tarefa

Your task here is to extract data on very bright and not hazardous asteroids. The code should satisfy two conditions:

'absolute_magnitude' is larger than or equal to 25;
'hazardous' is False.

After this, output the random 5 rows of the data_extracted.

Tarefa

Your task here is to extract data on very bright and not hazardous asteroids. The code should satisfy two conditions:

'absolute_magnitude' is larger than or equal to 25;
'hazardous' is False.

After this, output the random 5 rows of the data_extracted.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 2. Capítulo 3

Dealing With Several Conditions


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] > 3.5) & (data['hazardous'] == True)]
print(data_extracted)

In the output, you can see all the rows that satisfy these two conditions:

est_diameter_min > 3.5;
hazardous == True.


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] < 0.0005) | (data['est_diameter_max'] > 20)]
print(data_extracted)

In the output, you can see all the rows that satisfy one of these two conditions:

est_diameter_min < 0.0005;
est_diameter_max > 20.

Tarefa

Your task here is to extract data on very bright and not hazardous asteroids. The code should satisfy two conditions:

'absolute_magnitude' is larger than or equal to 25;
'hazardous' is False.

After this, output the random 5 rows of the data_extracted.

Tarefa

Your task here is to extract data on very bright and not hazardous asteroids. The code should satisfy two conditions:

'absolute_magnitude' is larger than or equal to 25;
'hazardous' is False.

After this, output the random 5 rows of the data_extracted.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] > 3.5) & (data['hazardous'] == True)]
print(data_extracted)

In the output, you can see all the rows that satisfy these two conditions:

est_diameter_min > 3.5;
hazardous == True.


              1234
            
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/planet', index_col = 0)
data_extracted = data.loc[(data['est_diameter_min'] < 0.0005) | (data['est_diameter_max'] > 20)]
print(data_extracted)

In the output, you can see all the rows that satisfy one of these two conditions:

est_diameter_min < 0.0005;
est_diameter_max > 20.

Tarefa

Your task here is to extract data on very bright and not hazardous asteroids. The code should satisfy two conditions:

'absolute_magnitude' is larger than or equal to 25;
'hazardous' is False.

After this, output the random 5 rows of the data_extracted.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Seção 2. Capítulo 3

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo