Зміст курсу

Advanced Techniques in pandas

1. Get Familiar With Indexing and Selecting Data

Output Columns by Title Output Rows by Index Select Specific Rows and Columns Learn More About Indexation Get Familiar With lambda Functions Expand Functionality of the .iloc[] Function

2. Dealing With Conditions

Set Condition Select Data Based on Condition Dealing With Several Conditions Make Your Code Beautiful Conditions Quiz

3. Extract Data

Is Data in ...?Combine Your Knowledge Between Function Extract Specific Data Find the Smallest Values of a Column Find the Largest Values of a Column Find the Correlation

4. Aggregating Data

Get Familiar With the .groupby() Method Group by Several Columns Complicated Grouping Group Dealing With Pivot Tables Create a Pivot Table

5. Preprocessing Data

Check for Missing Values Calculate the Number of Missing Values What Will We Do With the NaN Values?How to Delete Only NaN Values?Fill In the Missing Values Manage Categorical Variables Check the Column Type Manage an Incorrect Column Rename the Column

Advanced Techniques in pandas

Set Condition

In this section, we will learn how to extract data using specific conditions, but first I want you to examine the data set we will use. It includes data on asteroids:

	id	name	est_diameter_min	est_diameter_max	absolute_magnitude	hazardous
0	2162635	162635 (2000 SS164)	1.198271	2.679415	16.73	False
1	2277475	277475 (2005 WK4)	0.265800	0.594347	20.00	True
2	2512244	512244 (2015 YE18)	0.722030	1.614507	17.83	False
3	3596030	(2012 BV13)	0.096506	0.215794	22.20	False
4	3667127	(2014 GE35)	0.255009	0.570217	20.09	True

id - Unique identifier for each asteroid;
name - Name given by NASA;
est_diameter_min - Minimum estimated diameter in kilometers;
est_diameter_max - Maximum estimated diameter in kilometers;
absolute_magnitude - Describes how light the object is;
hazardous - Boolean feature that shows whether asteroid is harmful or not.

You are already familiar with the .loc[] function, but here we will expand its possibilities.

One of the most useful tools is to set conditions on a column to extract specific values. So, you just put the condition of the column inside the .loc[] function. Look at the several conditions and outputs.

data.loc[data['est_diameter_max'] < 0.005].head() - extracts the first five rows where the column values 'est_diameter_max' are less then 0.005;
data.loc[data['absolute_magnitude'] >= 30].head() - extracts the first five rows where the column values 'absolute_magnitude' are greater than or equal to 30.

Your task is to choose all correct forms of setting conditions on the column `'est_diameter_min'`. Please look; this column is numerical, so think about the conditions we can use with numbers.

Виберіть кілька правильних відповідей

Все було зрозуміло?

Секція 2. Розділ 1

Зміст курсу

Advanced Techniques in pandas

1. Get Familiar With Indexing and Selecting Data

Output Columns by Title Output Rows by Index Select Specific Rows and Columns Learn More About Indexation Get Familiar With lambda Functions Expand Functionality of the .iloc[] Function

2. Dealing With Conditions

Set Condition Select Data Based on Condition Dealing With Several Conditions Make Your Code Beautiful Conditions Quiz

3. Extract Data

Is Data in ...?Combine Your Knowledge Between Function Extract Specific Data Find the Smallest Values of a Column Find the Largest Values of a Column Find the Correlation

4. Aggregating Data

Get Familiar With the .groupby() Method Group by Several Columns Complicated Grouping Group Dealing With Pivot Tables Create a Pivot Table

5. Preprocessing Data

Advanced Techniques in pandas

Set Condition

In this section, we will learn how to extract data using specific conditions, but first I want you to examine the data set we will use. It includes data on asteroids:

	id	name	est_diameter_min	est_diameter_max	absolute_magnitude	hazardous
0	2162635	162635 (2000 SS164)	1.198271	2.679415	16.73	False
1	2277475	277475 (2005 WK4)	0.265800	0.594347	20.00	True
2	2512244	512244 (2015 YE18)	0.722030	1.614507	17.83	False
3	3596030	(2012 BV13)	0.096506	0.215794	22.20	False
4	3667127	(2014 GE35)	0.255009	0.570217	20.09	True

id - Unique identifier for each asteroid;
name - Name given by NASA;
est_diameter_min - Minimum estimated diameter in kilometers;
est_diameter_max - Maximum estimated diameter in kilometers;
absolute_magnitude - Describes how light the object is;
hazardous - Boolean feature that shows whether asteroid is harmful or not.

You are already familiar with the .loc[] function, but here we will expand its possibilities.

data.loc[data['est_diameter_max'] < 0.005].head() - extracts the first five rows where the column values 'est_diameter_max' are less then 0.005;
data.loc[data['absolute_magnitude'] >= 30].head() - extracts the first five rows where the column values 'absolute_magnitude' are greater than or equal to 30.

Your task is to choose all correct forms of setting conditions on the column `'est_diameter_min'`. Please look; this column is numerical, so think about the conditions we can use with numbers.

Виберіть кілька правильних відповідей

Все було зрозуміло?

Секція 2. Розділ 1

Advanced Techniques in pandas

Set Condition

Your task is to choose all correct forms of setting conditions on the column 'est_diameter_min'. Please look; this column is numerical, so think about the conditions we can use with numbers.

Виберіть кілька правильних відповідей

Advanced Techniques in pandas

Set Condition

Your task is to choose all correct forms of setting conditions on the column 'est_diameter_min'. Please look; this column is numerical, so think about the conditions we can use with numbers.

Виберіть кілька правильних відповідей

Your task is to choose all correct forms of setting conditions on the column `'est_diameter_min'`. Please look; this column is numerical, so think about the conditions we can use with numbers.

Your task is to choose all correct forms of setting conditions on the column `'est_diameter_min'`. Please look; this column is numerical, so think about the conditions we can use with numbers.