keywords: data wrangling, python, jupyter notebook, pandas, excel, csv
This project cleans and concatenates the results of IT salary surveys made by sysarmy in South America.
- Salary surveys:
- /data/input/2015_2.csv: Link
- /data/input/2016_1.csv: Link
- /data/input/2016_2.xlsx: Link
- /data/input/2017_1.xlsx: Link
- /data/input/2017_2.xlsx: Link
- /data/input/2018_1.xlsx: Link
- /data/input/2018_2.xslx: Link
- /data/input/2019_1.xslx: Link
- /data/input/2019_2.xslx: Link Argentina - Link LATAM
- /data/input/2020_1.xslx: Link Argentina - Link LATAM
- Currencies data
- /data/input/USDARS_CUR.json: Link
- /data/input/USDBOB_CUR.json: Link
- /data/input/USDCLP_CUR.json: Link
- /data/input/USDCOP_CUR.json: Link
- /data/input/USDCRC_CUR.json: Link
- /data/input/USDCUP_CUR.json: Link
- /data/input/USDDOP_CUR.json: Link
- /data/input/USDGTQ_CUR.json: Link
- /data/input/USDHNL_CUR.json: Link
- /data/input/USDMXN_CUR.json: Link
- /data/input/USDNIO_CUR.json: Link
- /data/input/USDPAB_CUR.json: Link
- /data/input/USDPEN_CUR.json: Link
- /data/input/USDPYG_CUR.json: Link
- /data/input/USDUYU_CUR.json: Link
- /data/input/USDVEF_CUR.json: Link
- /data/output/encuestas.csv: unified, cleaned and normalized dataset with the salary surveys results.
- sysarmy_sueldos_wrangling.ipynb: Jupyter Notebook that contains details and codes for the data wrangling process.
- sysarmy_sueldos_wrangling.yml: Configuration file
- experiencia a números enteros
- antiguedad a números enteros
- normalizar/categorizar trabajo
- normalizar/categorizar discapacidad
- normalizar/categorizar eventos_tecnologia
- I took some ideas from this project: https://github.com/gerardobort/sysarmy-data