# Lesson 16

## Boolean Selection¶

This lesson covers:

• Boolean selection
• where

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# Setup: Load the momentum data

import numpy as np
import pandas as pd



### Problem: Selecting rows with boolean conditions¶

Select the rows in momentum where all returns on a day are negative.

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### Problem: Selecting rows¶

Select the rows in momentum where 50% or more of the returns on a day are negative.

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### Problem: Selecting columns¶

Select the columns in momentum what have the smallest and second smallest average returns.

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### Problem: Selecting rows and columns¶

Select the returns for the column with the single most negative return on days where all of the returns are negative.

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### Problem: Selecting Elements using Logical Statements¶

For portfolio 1 and portfolio 10 compute the correlation when both returns are negative and when both are positive.

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# Setup: Reproducible random numbers

rs = np.random.RandomState(19991231)
x = rs.randint(1, 11, size=(10,3))
x


### Problem: Select the columns of x that means >= $E[x]$¶

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### Problem: Select the rows of x that means >= $E[x]$¶

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### Problem: Select the rows and column of x where both have means < $E[x]$¶

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### Problem: Using where¶

Use where to select the index of the elements in portfolio 5 that are negative. Next, use the where command in its two output form to determine which elements of the portfolio return matrix are less than -2%.

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### Exercises¶

#### Exercise: Select the Most Volatile Portfolio¶

Select the column in momentum that has the highest standard deviation.

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#### Exercise: Select the High Kurtosis Portfolios¶

Select the columns that have kurtoses above the median kurtosis.

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#### Exercise: Select¶

Select the rows where all of the returns in the row are less than the 25% quantile for their portfolio.

Note: Comparisons between DataFrames and Series works like mathematical operations (+, -, etc.).

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