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Original file line number	Diff line number	Diff line change
`@@ -66,6 +66,8 @@ import pandas as pd`
`66`	`66`	`import statsmodels.api as sm`
`67`	`67`	`from statsmodels.iolib.summary2 import summary_col`
`68`	`68`	`from linearmodels.iv import IV2SLS`
	`69`	`+import seaborn as sns`
	`70`	`+sns.set_theme()`
`69`	`71`	```
`70`	`72`
`71`	`73`	`### Prerequisites`
`@@ -100,8 +102,6 @@ between GDP per capita and the protection against`
`100`	`102`	`expropriation index`
`101`	`103`
`102`	`104`	```{code-cell} python3
`103`		`-plt.style.use('seaborn')`
`104`		`-`
`105`	`105`	`df1.plot(x='avexpr', y='logpgp95', kind='scatter')`
`106`	`106`	`plt.show()`
`107`	`107`	```
@@ -701,4 +701,4 @@ for $\beta$, however `.solve()` is preferred as it involves fewer
`701`	`701`	`computations.`
`702`	`702`
`703`	`703`	```{solution-end}
`704`		-```
	`704`	+```

Original file line number	Diff line number	Diff line change
`@@ -361,15 +361,16 @@ Using this series, we can plot the average real minimum wage over the`
`361`	`361`	`past decade for each country in our data set`
`362`	`362`
`363`	`363`	```{code-cell} ipython
`364`		`-%matplotlib inline`
`365`	`364`	`import matplotlib.pyplot as plt`
`366`		`-plt.rcParams["figure.figsize"] = (11, 5) #set default figure size`
`367`		`-import matplotlib`
`368`		`-matplotlib.style.use('seaborn')`
	`365`	`+import seaborn as sns`
	`366`	`+sns.set_theme()`
	`367`	+```
`369`	`368`
`370`		`-merged.mean().sort_values(ascending=False).plot(kind='bar', title="Average real minimum wage 2006 - 2016")`
	`369`	+```{code-cell} ipython
	`370`	`+merged.mean().sort_values(ascending=False).plot(kind='bar',`
	`371`	`+ title="Average real minimum wage 2006 - 2016")`
`371`	`372`
`372`		`-#Set country labels`
	`373`	`+# Set country labels`
`373`	`374`	`country_labels = merged.mean().sort_values(ascending=False).index.get_level_values('Country').tolist()`
`374`	`375`	`plt.xticks(range(0, len(country_labels)), country_labels)`
`375`	`376`	`plt.xlabel('Country')`
`@@ -468,12 +469,10 @@ minimum wages in 2016 for each continent.`
`468`	`469`	`object`
`469`	`470`
`470`	`471`	```{code-cell} python3
`471`		`-import seaborn as sns`
`472`		`-`
`473`	`472`	`continents = grouped.groups.keys()`
`474`	`473`
`475`	`474`	`for continent in continents:`
`476`		`- sns.kdeplot(grouped.get_group(continent).loc['2015'].unstack(), label=continent, shade=True)`
	`475`	`+ sns.kdeplot(grouped.get_group(continent).loc['2015'].unstack(), label=continent, fill=True)`
`477`	`476`
`478`	`477`	`plt.title('Real minimum wages in 2015')`
`479`	`478`	`plt.xlabel('US dollars')`
`@@ -617,4 +616,4 @@ plt.show()`
`617`	`616`	```
`618`	`617`
`619`	`618`	```{solution-end}
`620`		-```
	`619`	+```

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