Clarifying challenge and removing unnecessary step

villanueval · villanueval · commit 40c991566c78 · 2019-02-20T14:38:00.000-05:00
Setting sex to x is not used in the next step of the challenge.
diff --git a/_episodes/03-index-slice-subset.md b/_episodes/03-index-slice-subset.md
@@ -529,8 +529,9 @@ asking Python to select rows that have a `NaN` value of weight.
 > ## Challenge - Putting it all together
 >
 > 1. Create a new DataFrame that only contains observations with sex values that
->   are **not** female or male. Assign each sex value in the new DataFrame to a
->   new value of 'x'. Determine the number of null values in the subset.
+>   are **not** female or male. Print the number of rows in this new DataFrame.
+>   Verify the result by comparing the number of rows in the new DataFrame with
+>   the number of rows in the surveys DataFrame where sex is null.
 >
 > 2. Create a new DataFrame that contains only observations that are of sex male
 >   or female and where weight values are greater than 0. Create a stacked bar

Original file line number	Diff line number	Diff line change
@@ -529,8 +529,9 @@ asking Python to select rows that have a `NaN` value of weight.
`529`	`529`	`> ## Challenge - Putting it all together`
`530`	`530`	`>`
`531`	`531`	`> 1. Create a new DataFrame that only contains observations with sex values that`
`532`		`-> are not female or male. Assign each sex value in the new DataFrame to a`
`533`		`-> new value of 'x'. Determine the number of null values in the subset.`
	`532`	`+> are not female or male. Print the number of rows in this new DataFrame.`
	`533`	`+> Verify the result by comparing the number of rows in the new DataFrame with`
	`534`	`+> the number of rows in the surveys DataFrame where sex is null.`
`534`	`535`	`>`
`535`	`536`	`> 2. Create a new DataFrame that contains only observations that are of sex male`
`536`	`537`	`> or female and where weight values are greater than 0. Create a stacked bar`