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[inequality] Update exercise 3 #498

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Jul 5, 2024
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[inequality] Update exercise 3 #498

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6daf793
[inequality] Update exercise 3
longye-tian Jul 2, 2024
73aab7b
Update inequality.md
longye-tian Jul 2, 2024
f3c282b
Update inequality.md
longye-tian Jul 2, 2024
384a3d9
Update inequality.md
longye-tian Jul 2, 2024
f22b53d
add data.ipynb and delete to csv
longye-tian Jul 4, 2024
3653c62
remove skip-execution code as it is not compatible with google collab
mmcky Jul 4, 2024
395657e
test the problem
longye-tian Jul 4, 2024
15d1ae6
Revert "test the problem"
longye-tian Jul 4, 2024
a28f57c
test google colab RAM
longye-tian Jul 4, 2024
bbab6ca
change link to notebook on github
mmcky Jul 5, 2024
0aec0eb
Merge branch 'inequality_exercise' of https://github.com/QuantEcon/le…
mmcky Jul 5, 2024
971b327
update_inequality_exercise
longye-tian Jul 5, 2024
6e2d53e
update year in the text
longye-tian Jul 5, 2024
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6 changes: 3 additions & 3 deletions lectures/inequality.md
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Original file line number Diff line number Diff line change
Expand Up @@ -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.
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@longye-tian can we either change 1990 in the text to 2016 or the otherway around based on the correct context?


```{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
Expand All @@ -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`
Expand All @@ -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

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