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188 | 188 | "source": [
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189 | 189 | "🔔 **Question**: Let's take a look at the final data frame.\n",
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190 | 190 | "\n",
|
191 |
| - "1. How many rows and columns are there in the total dataframe?\n", |
| 191 | + "1. <span style=\"color:purple\"> How many rows and columns are there in the concatenated DataFrame?</span>\n", |
192 | 192 | "2. How many numeric columns are there in the dataset?\n",
|
193 |
| - "3. What data type are the values in the `poverty_level` column?" |
| 193 | + "3. What data type are the values in the `poverty_level` column?\n" |
194 | 194 | ]
|
195 | 195 | },
|
196 | 196 | {
|
|
259 | 259 | "## 🥊 Challenge 4: Count Values\n",
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260 | 260 | "The first thing we will want to do is count values of some features. \n",
|
261 | 261 | "1. Run `value_counts()` on the `poverty_level` column. \n",
|
262 |
| - "2. Look at the [documentation](https://pandas.pydata.org/docs/reference/api/pandas.Series.value_counts.html) to see how you can normalize the output of `value_counts()`." |
| 262 | + "2. <span style=\"color:purple\"> Look through the [documentation](https://pandas.pydata.org/docs/reference/api/pandas.Series.value_counts.html) and **normalize** the output of `value_counts()`.</span>" |
263 | 263 | ]
|
264 | 264 | },
|
265 | 265 | {
|
|
344 | 344 | "source": [
|
345 | 345 | "## 🥊 Challenge 8: Bar Plot of Value Counts\n",
|
346 | 346 | "\n",
|
347 |
| - "Finally, let's create our bar plots. Fill in the blanks below, following the steps.\n", |
| 347 | + "Finally, let's create our bar plots. Fill in the blanks below, following the steps. \n", |
348 | 348 | "\n",
|
349 | 349 | "1. Run a **normalized** `value_counts()` on the `general_health` column of `df_above`.\n",
|
350 |
| - "2. Run `plot()` on the output of the resulting DataFrame. Enter the values for two arguments: `kind` must be set to `bar`, and `alpha` must be set to `.5`." |
| 350 | + "2. Run `plot()` on the output of the resulting DataFrame. Enter the values for two arguments: `kind` must be set to `bar`, and `alpha` must be set to `.5`.\n" |
351 | 351 | ]
|
352 | 352 | },
|
353 | 353 | {
|
|
363 | 363 | "df_below['general_health'].value_counts(normalize=True).plot(kind=..., alpha=...,color='maroon');"
|
364 | 364 | ]
|
365 | 365 | },
|
| 366 | + { |
| 367 | + "cell_type": "markdown", |
| 368 | + "metadata": {}, |
| 369 | + "source": [ |
| 370 | + "🔔 <span style=\"color:purple\"> **Question**: What is the `alpha` parameter doing? Read through the [documentation](https://pandas.pydata.org/docs/user_guide/visualization.html) to find out.</span>" |
| 371 | + ] |
| 372 | + }, |
366 | 373 | {
|
367 | 374 | "cell_type": "markdown",
|
368 | 375 | "metadata": {},
|
|
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