update_inequality_exercise

Hi Matt,

This commit select 3000 random sample from the original dataset.

Best,
Longye

Author: longye-tian

lectures/inequality.md

@@ -1084,7 +1084,7 @@ df_income_wealth.head(n=4)
 We will focus on wealth variable `n_wealth` to compute a Gini coefficient for the year 1990.
 
 ```{code-cell} ipython3
-data = df_income_wealth[df_income_wealth.year == 2016]
+data = df_income_wealth[df_income_wealth.year == 2016].sample(3000, random_state=1)
 ```
 
 ```{code-cell} ipython3
@@ -1094,7 +1094,7 @@ data.head(n=2)
 We can first compute the Gini coefficient using the function defined in the lecture above.
 
 ```{code-cell} ipython3
-gini_coefficient(data.n_wealth.values[1:3000])
+gini_coefficient(data.n_wealth.values)
 ```
 
 Now we can write a vectorized version using `numpy`
@@ -1108,7 +1108,7 @@ def gini(y):
     return g_sum / (2 * n * np.sum(y))
 ```
 ```{code-cell} ipython3
-gini(data.n_wealth.values[1:3000])
+gini(data.n_wealth.values)
 ```
 Let's simulate five populations by drawing from a lognormal distribution as before