{"id":13507188,"url":"https://github.com/JordiPolo/dataframe","last_synced_at":"2025-03-30T07:32:28.297Z","repository":{"id":57488302,"uuid":"66136897","full_name":"JordiPolo/dataframe","owner":"JordiPolo","description":"Package providing functionality similar to Python's Pandas or R's 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and Data structures"],"sub_categories":[],"readme":"# Dataframe\n[![Build\nStatus](https://travis-ci.org/JordiPolo/dataframe.svg?branch=master)](https://travis-ci.org/JordiPolo/dataframe)\n\nDataFrame is a library that implements an API similar to [Python's Pandas](http://pandas.pydata.org/) or [R's data.frame()](http://www.r-tutor.com/r-introduction/data-frame).\n\n## Installation\n\nAdd `dataframe` to your list of dependencies in `mix.exs`:\n\n```\ndef deps do\n [{:dataframe, \"~\u003e 0.1.0\"}]\nend\n```\n\n\n## Usage\n\n### Tutorials\n\n- [Lesson 1](tutorial/lesson1.md)\n\n\n### Creation\n```elixir\ndata = DataFrame.new(DataFrame.Table.build_random(6,4), [1,3,4,5], DataFrame.DateRange.new(\"2016-09-12\", 6))\n```\n\noutput:\n```\n 1 3 4 5\n2016-09-12 0.3216495192 0.3061978162 0.5240627861 0.3014870998\n2016-09-13 0.7085624128 0.1027917034 0.0274851281 0.4999253931\n2016-09-14 0.5409299230 0.7234486655 0.0902951353 0.9265397862\n2016-09-15 0.8144437609 0.7566869039 0.5943981962 0.4555049347\n2016-09-16 0.0228473208 0.9033617026 0.6984988237 0.9858222366\n2016-09-17 0.6401066584 0.2700256640 0.4256911712 0.1085587668\n```\n\n### Exploring\n```elixir\nDataFrame.head(data, 2)\n```\n```\n 1 3 4 5\n2016-09-12 0.3216495192 0.3061978162 0.5240627861 0.3014870998\n2016-09-13 0.7085624128 0.1027917034 0.0274851281 0.4999253931\n```\n\n```elixir\nDataFrame.tail(data, 1)\n```\n```\n 1 3 4 5\n2016-09-17 0.6401066584 0.2700256640 0.4256911712 0.1085587668\n```\n\n```elixir\nDataFrame.describe(data)\n```\n```\n 1 3 4 5\ncount 6 6 6 6\nmean 0.6465539263 0.5159964091 0.3872831261 0.3932447202\nstd 0.1529956837 0.3280592207 0.1795171140 0.3121805879\nmin 0.4016542004 0.0206350637 0.0337014209 0.0177659020\n25% 0.6282734986 0.5048574951 0.3799407685 0.2747983874\n50% 0.7006870983 0.6401629955 0.4141661547 0.4043847826\n75% 0.7412280866 0.6620905719 0.4517382532 0.4916518963\nmax 0.8024114094 0.9682031054 0.6199458675 0.8934404147\n```\n\n### Transposing\n\n```elixir\nDataFrame.transpose(data)\n```\n```\n 2016-09-12 2016-09-13 2016-09-14 2016-09-15 2016-09-16 2016-09-17\n1 0.3216495192 0.7085624128 0.5409299230 0.8144437609 0.0228473208 0.6401066584\n3 0.3061978162 0.1027917034 0.7234486655 0.7566869039 0.9033617026 0.2700256640\n4 0.5240627861 0.0274851281 0.0902951353 0.5943981962 0.6984988237 0.4256911712\n5 0.3014870998 0.4999253931 0.9265397862 0.4555049347 0.9858222366 0.1085587668\n```\n\n### Sorting\n\nSorting index (defaults bigger to smaller)\n```elixir\nDataFrame.sort_index(data)\n```\n```\n 1 3 4 5\n2016-09-17 0.6401066584 0.2700256640 0.4256911712 0.1085587668\n2016-09-16 0.0228473208 0.9033617026 0.6984988237 0.9858222366\n2016-09-15 0.8144437609 0.7566869039 0.5943981962 0.4555049347\n2016-09-14 0.5409299230 0.7234486655 0.0902951353 0.9265397862\n2016-09-13 0.7085624128 0.1027917034 0.0274851281 0.4999253931\n2016-09-12 0.3216495192 0.3061978162 0.5240627861 0.3014870998\n```\n\nSorting by a column (false to sort smaller to bigger)\n```elixir\nDataFrame.sort_values(data, 4, false)\n```\n```\n 1 3 4 5\n2016-09-13 0.7085624128 0.1027917034 0.0274851281 0.4999253931\n2016-09-14 0.5409299230 0.7234486655 0.0902951353 0.9265397862\n2016-09-17 0.6401066584 0.2700256640 0.4256911712 0.1085587668\n2016-09-12 0.3216495192 0.3061978162 0.5240627861 0.3014870998\n2016-09-15 0.8144437609 0.7566869039 0.5943981962 0.4555049347\n2016-09-16 0.0228473208 0.9033617026 0.6984988237 0.9858222366\n```\n\n### Selecting\n\nBy name:\n```elixir\nDataFrame.loc(data, DataFrame.DateRange.new(\"2016-09-15\", 2), [3,4])\n```\n```\n 3 4\n2016-09-15 0.5417848216 0.5546980818\n2016-09-16 0.6621771048 0.5763923325\n```\n\nA specific data by name:\n```elixir\nDataFrame.at(data, \"2016-09-15\", 4)\n```\n```\n0.5546980818725673\n```\n\n\nBy position:\n```elixir\nDataFrame.iloc(data, 4..6, 2..4)\n```\n```\n 4 5\n2016-09-16 0.6984988237 0.9858222366\n2016-09-17 0.4256911712 0.1085587668\n```\n\n```elixir\nDataFrame.iat(data, 0, 0)\n```\n```\n0.31553155828919915\n```\n\nThe library is in very early stages of development. No effort has been made to optimize its performance. Expect it to be slow.\n\n### Plotting\n\nIf you have Python and Matplotlib you can plot the data in your Dataframe.\nCheck out the [Explot](https://github.com/JordiPolo/explot) package for installation details.\n\nLet's plot the cummulative sum of the values:\n\n```\n data |\u003e DataFrame.cumsum |\u003e DataFrame.plot\n```\n\nWill give us this graph:\n![](readme_example.png)\n\n\n## Development\n\nRun tests\n```\nmix test\n```\n\n## TODO\n\n- Deal with exceptions (negative numbers as input, etc.)\n- Setting of subtable data\n- Types of columns (no stat data on text, etc)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FJordiPolo%2Fdataframe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FJordiPolo%2Fdataframe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FJordiPolo%2Fdataframe/lists"}