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1. Concepts & Definitions
1.1. Experiment, observation, and sample space
1.2. Sample space: Venn and Tree diagram
1.3. Simple and composite events
1.4. Three definitions of probability
1.5. Law of large numbers and its consequences
1.6. Frequency and empirical probability
2. Problem & Solution
2.4. Frequency of categories from tables
2.5. Simple and marginal probabilities
2.6. Conditional probabilities
How to extract data using WITS API
How to extract data using WITS API
The following steps will serve as a guideline to create a six-face dice simulator in Python programming language:
Load the notebook with commands developed in step 2.2. (click on the link):
https://colab.research.google.com/drive/1mUX_ItyQzRGUC3qqjjCijTFzOW4TCIdL?usp=sharing
Let's check what are the products categories employed in customs using WITS database. First, it is necessary to install WITS API:
!pip install world_trade_data --upgrade
The following values will be stored in variable coin_seq:
Collecting world_trade_data Downloading world_trade_data-0.1.1.tar.gz (11 kB) Preparing metadata (setup.py) ... done
...Successfully built world_trade_data Installing collected packages: xmltodict, world_trade_data Successfully installed world_trade_data-0.1.1 xmltodict-0.13.0
The next sequences of commands are useful to obtain iso3Code and the name for each country:
import pandas as pd
import world_trade_data as wits
pd.set_option('display.max_rows', 6)
df_countries = wits.get_countries()
df_countries = df_countries.reset_index()
df_countries
The following table with values will appear:
Obtain the exportation values of Brazil (BRA) to all countries (ALL) in a table format:
bra_exports_2020 = wits.get_indicator('XPRT-TRD-VL', partner='all', reporter='bra', year='2020')
bra_exports_2020 = bra_exports_2020.reset_index()
bra_exports_2020
Obtain the exportation values of Brazil (BRA) aggregated per values of 'ProductCode' column:
bra_exports_2020_grouped_per_product = bra_exports_2020.groupby('ProductCode').aggregate({'Value':'sum'}).reset_index(drop=False)
bra_exports_2020_grouped_per_product
Obtain the first six greatest values in column 'Value' using aggregated values in 'ProductCode' column:
bra_exports_2020_grouped_per_product = bra_exports_2020_grouped_per_product.sort_values(by='Value', ascending=False)
bra_exports_2020_grouped_per_product.head(6)
The previous tables give insights to select certain categories of products according to their 'ProductCode'. In fact, there is a system called Harmony System (HS) Code which can be useful. More about HS code is explained in:
https://www.trade.gov/harmonized-system-hs-codes
https://icecargo.com.au/hs-codes-beginners-guide/
https://customs.gov.tl/doing-business/hs-code-tariff-and-incoterms/
The Python code with all the steps is summarized in this Google Colab (click on the link):
https://colab.research.google.com/drive/1mUX_ItyQzRGUC3qqjjCijTFzOW4TCIdL?usp=sharing
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