Course Content
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 then0.005
.
data.loc[data['absolute_magnitude'] >= 30].head()
- extracts the first five rows where the column values'absolute_magnitude'
are greater than or equal to30
.
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
Section 2.
Chapter 1