Advanced filtering using metadata¶
The metadata() function¶
Now that you have knowledge of some of the metadata of Ipeadata, let’s introduce yourself to a function called metadata(). This function returns all Ipeadata’s time series in a data frame, similarly to the list_series() function. However, the difference between the two functions is that metadata() returns not only the time series but also their metadata. You might then be asking yourself why these two functions exists, since metadata() is a more complete version of the list_series() function (metadata() features all of the list_series() information plus metadata). The answer is: list_series() is intended to be a more simplistic version, aiming unexperienced users and designed to be friendly to them. metadata(), in fact, is a more complete version as well as more confusing because of the quantity of information returned. No more words, let’s run the function:
>>> ipeadatapy.metadata()
BIG THEME SOURCE SOURCE ACRONYM ... SERIES STATUS THEME CODE MEASURE
0 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
1 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
2 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
3 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Cabe?a
4 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Cabe?a
5 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Cabe?a
6 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... I 1 Tonelada
7 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
8 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
9 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
10 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
11 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
12 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Tonelada
13 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... I 1 Tonelada
14 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... I 1 Cabe?a
15 Macroecon?mico Instituto Brasileiro de Geografia e Estat?stic... IBGE/Coagro ... A 1 Cabe?a
... ... ... ... ... ... ... ...
[8549 rows x 15 columns]
Better filtering with metadata()¶
Why is this function so powerful and important? The first obvious answer is: it gives you more informations about time series. The not-so-obvious answer is: it allows you to better filter time series from Ipeadata. Let’s state an illustrative problem for better understanding:
Ipeadata API has 8565 time series in total. Let’s suppose you are doing research in macroeconomics about the United States, but for some specific reason, your interest in data is restricted to data published by The Economist. It also needs to be quarterly published. How to solve this problem using ipeadatapy Python package?
>>> ipeadatapy.metadata(big_theme="Macroecon?mico", country="USA", source="Economist", frequency="Trimestral")
BIG THEME SOURCE SOURCE ACRONYM SOURCE URL UNIT ... NAME NUMERICA SERIES STATUS THEME CODE MEASURE
5585 Macroecon?mico The Economist Economist www.economist.com bilh?es ... balan?o - conta corrente - saldo (acum. 12 meses) True I 11 US$
5586 Macroecon?mico The Economist Economist www.economist.com None ... PIB - var. real trimestral anualiz. True A 11 (% a.a.)
5587 Macroecon?mico The Economist Economist www.economist.com None ... PIB - var. real contra igual trimestre do ano ... True A 11 (% a.a.)
[3 rows x 15 columns]
Gotcha! Other metadata also can be used as filtering parameters. For all parameters run help(idpy.metadata).