Useful crystal-ball-related stuff.
If you have hundreds of csvs you need to quickly digest and understand, you can use crystal-ball to help with the onboarding and data exploration phase of your project. You will be able to immediately dive into an expansive data set without getting lost.
find specific columns and tables you may be interested in, but may have otherwise not known where to look.
walk through connections between different csvs,
compare and establish foreign key and primary key relationships by using simple boxplots
dynamically create a master table of useful information while simultaneously recording your step-by-step process for future reference.
Installation and Usage
pip install crystal-ball</programlisting> You can start using CrystalBall right away by importing it and initializing it with a relative directory containing the CSVs.
import crystalball as cb ball = cb.run("insert relative directory here")
Note that all methods that involve searching via keynames are case sensitive.
cb.contains(keywords: list, all_colnames: list=None) → list
Check if keywords exist in all_colnames.
cb.featureSearch(keywords: list, all_colnames: list=None) → list
Find the columns that contain the keywords.
cb.tableSearch(keywords: list, csvname_to_colnames_list=None, mode: str=UNION) → list
Find the tables that contain the keywords.
cb.openTable(rel_dir: str, indices: list=) → DataFrame
Open the csv that is referenced by the given relative directory.
cb.subTable(supertable: DataFrame, chosen_index: list, chosen_columns: list) → DataFrame
Create a subtable from a supertable.
cb.mergeTables(tables: list) → DataFrame
Sequentially merge a list of tables that all share a common index.
cb.analyzeRelationships(to_analyze: list, visualize: bool=True) → DataFrame
Analyze basic stats of one or more different Series.
compareRelationship(to_analyze1: Series, to_analyze2: Series, visualize: bool=False) → DataFrame
Compare and contrast the difference between two Series.
cb.export(df_to_export: DataFrame, write_to: str, export_type: str=CSV) → None
Exports contents of dataframe to relative location specified by write_to arg.
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