You can work with a Jupyter
notebook using Stata
just as you would using Python. Text and math can be written in Markdown as we have done in the other notebooks. So, use your usual Stata
code in code cells
, produce figures etc., as if you were in the Stata
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You can work with Stata
in a Python
notebook by using the package ipystata
. Just like r2py
, which allows us to use R
in Python
, we can now use both (or if you want all three!) programming languages in one notebook.
Let's start by importing all the packages we want to use.
more ...We have studied the theory of dynamic programming in discrete time under certainty. Let's review what we know so far, so that we can start thinking about how to take to the computer.
We want to find a sequence $\{x_t\}_{t=0}^\infty$ and a function $V^*:X\to\mathbb{R}$ such that
$$V^{\ast}\left(x_{0}\right)=\sup\limits _{\left\{ x_{t}\right\} _{t=0}^{\infty}}\sum\limits _{t=0}^{\infty}\beta^{t}U(x_{t},x_{t+1})$$ more ...This notebook will introduce you to working with data in Python
. You will use packages like Numpy
to manipulate, work and do computations with arrays, matrices, and such, and anipulate data (see my Introduction to Python). But given the needs of economists (and other scientists) it will be advantageous for us to use pandas
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There are many sources of GIS data. Here are some useful links:
GIS refers to methods of storing, displaying and analyzing geogaphical information. These methods have become essential in economic analysis (as you have noticed from the reading list for our Ph.D. course on economic growth). For this reason, it is good that you acquaint yourself with these methods. They will prove very useful when doing research, especially to show the spatial distribution of your variables of interest, contructing new measures, or doing spatial analysis.
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