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Setting Condition | Dealing With Conditions
Advanced Techniques in pandas
course content

Course Content

Advanced Techniques in pandas

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data
2. Dealing With Conditions
3. Extracting Data
4. Aggregating Data
5. Preprocessing Data

bookSetting 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 - 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[] attribute, 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[] attribute. 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.

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.

Select a few correct answers

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Section 2. Chapter 1
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