Set Condition | Dealing With Conditions

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.

Selecciona unas respuestas correctas

¿Todo estuvo claro?

Sección 2. Capítulo 1

Contenido del Curso

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.

Selecciona unas respuestas correctas

¿Todo estuvo claro?

Sección 2. Capítulo 1