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Advanced Techniques in pandas

Dealing With Several ConditionsDealing 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:

Sign Usage Python Example Equivalent in Boolean Statements
& This is used when we want to make the first and the second conditions satisfied. data.loc[condition_1 & condition_2] and
| This is used when we want to make the first or the second conditions satisfied. data.loc[condition_1 | condition_2] or

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.

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:

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.

Task

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.

Everything was clear?

Section 2. Chapter 3
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