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dexplo

A data analysis library comparible to pandas

Main Goals

  • A very minimal set of features

  • Be as explicit as possible

  • There should be one– and preferably only one –obvious way to do it.

Data Structures

  • Only DataFrames

  • No Series

Data Types

  • Only primitive types - int, float, boolean, numpy.unicode

  • No object data types

Row and Column Labels

  • No index, meaning no row labels

  • No hierarchical index

  • Column names must be strings

  • Column names must be unique

  • Columns stored in a numpy array

Subset Selection

  • Only one way to select data - [ ]

  • Subset selection will be explicit and necessitate both rows and columns

  • Rows will be selected only by integer location

  • Columns will be selected by either label or integer location. Since columns must be strings, this will not be amibguous

  • Column names cannot be duplicated

All selections and operations copy

  • All selections and operations provide new copies of the data

  • This will avoid any chained indexing confusion

Development

  • Must use type hints

  • Must use 3.6 - fstrings

  • Must have numpy, bottleneck, numexpr

Small feature set

  • Implement as few attributes and methods as possible

  • Focus on good idiomatic cookbook examples for doing more complex tasks

Only Scalar Data Types

No complex Python data types - [x] bool - always 8 bits, not-null - [x] int - always 64 bits, not-null - [x] float - always 64 bits, nulls allowed - [x] str - A python unicode object, nulls allowed - [ ] categorical - [ ] datetime - [ ] timedelta

Attributes to implement

  • [x] size

  • [x] shape

  • [x] values

  • [x] dtypes

May not implement any of the binary operators as methods (add, sub, mul, etc…)

Methods

Stats - [x] abs - [x] all - [x] any - [x] argmax - [x] argmin - [x] clip - [ ] corr - [x] count - [ ] cov - [x] cummax - [x] cummin - [ ] cumprod - [x] cumsum - [ ] describe - [x] max - [x] min - [x] median - [x] mean - [ ] mode - [ ] nlargest - [ ] nsmallest - [ ] quantile - [ ] rank - [x] std - [x] sum - [x] var - [ ] unique - [ ] nunique

Selection - [ ] drop - [ ] drop_duplicates - [x] head - [ ] isin - [ ] sample - [x] select_dtypes - [x] tail - [ ] where

Missing Data - [ ] isna - [ ] dropna - [ ] fillna - [ ] interpolate

Other - [ ] append - [ ] apply - [ ] assign - [x] astype - [ ] groupby - [ ] info - [ ] melt - [ ] memory_usage - [ ] merge - [ ] pivot - [ ] replace - [ ] rolling - [ ] sort_values

Functions - [ ] read_csv - [ ] read_sql - [ ] concat

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