Python Code - Basic

Python is a powerful tool for accounting research and data analytics. On this webpage, I share some python code snippets that I use often (and I forget). The snippets are mainly relevant to the following topics:

Data wrangling;
Visualization;
Regular expression;
Textual analysis;
Web-scraping.

All code files are stored here. Check anything you’re interested in:

Python functions.
- zip(): useful when turning (a1,a2,..), (b1,b2..),… into ((a1,b1), (a2, b2),..).
- map(): useful when executing a function for multiple iterable objects.
Pandas.
- agg(): useful when aggregating variables by groups.
- apply(): useful when executing a function for multiple columns.
- crosstab(): useful when preparing frequency table.
- cut(): useful when segmenting and sorting data values into bins. Notably, bin widths don’t have to be the same.
- fillna(): (coming soon).
- groupby().
- melt(): wide-form to long-form.
- options and settings: e.g., the maximum columns and rows to display.
- pivot (coming soon).
- pivot_table(): useful when preparing frequency table.
- sidetable: useful when displaying cumulative distributions.
- value_counts(): useful when preparing frequency table.
- zfill(): (coming soon).
- Reshaping: imbalanced to balanced panel.
FinanceDataReader: to download historical stock return data of US firms, etc.
SQL in Python (sqlite3).
- Introduction to SQL: Part I.
- Introduction to SQL: Part II.
Regular expression (regex) - coming soon.
geopandas - coming soon.
Webscraping.
- pandas.read_html().
- requests (coming soon).
- beautifulsoup (coming soon).
- selenium (coming soon).
Visualization.
- barplot() (coming soon).
- stacked barplot using pandas - useful for yearly distribution by groups (the code need replacing with a simpler one).
- countplot() (coming soon).
- lineplot().
- areaplot().
- jointplot().
- regplot().
- lmplot().
- heatmaplot(), useful for correlation table.