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examples","Python","Real life examples","特征工程"],"sub_categories":["Websites formats"],"readme":"# Skimpy\n\nA light weight tool for creating summary statistics from dataframes.\n![png](docs/logo.png)\n\n![](logo.png)\n\n[![PyPI](https://img.shields.io/pypi/v/skimpy.svg)](https://pypi.org/project/skimpy/)\n[![Status](https://img.shields.io/pypi/status/skimpy.svg)](https://pypi.org/project/skimpy/)\n[![Python Version](https://img.shields.io/pypi/pyversions/skimpy)](https://pypi.org/project/skimpy)\n[![License](https://img.shields.io/pypi/l/skimpy)](https://opensource.org/licenses/MIT)\n[![Read the documentation at https://aeturrell.github.io/skimpy/](https://img.shields.io/badge/docs-passing-brightgreen)](https://aeturrell.github.io/skimpy/)\n[![Tests](https://github.com/aeturrell/skimpy/workflows/Tests/badge.svg)](https://github.com/aeturrell/skimpy/actions?workflow=Tests)\n[![Codecov](https://codecov.io/gh/aeturrell/skimpy/branch/main/graph/badge.svg)](https://codecov.io/gh/aeturrell/skimpy)\n[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit\u0026logoColor=white)](https://github.com/pre-commit/pre-commit)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\n[![Google Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/gist/aeturrell/7bf183c559dc1d15ab7e7aaac39ea0ed/skimpy_demo.ipynb)\n[![Downloads](https://static.pepy.tech/badge/skimpy)](https://pepy.tech/projects/skimpy)\n[![Source](https://img.shields.io/badge/source%20code-github-lightgrey?style=for-the-badge)](https://github.com/aeturrell/skimpy)\n\n![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge\u0026logo=linux\u0026logoColor=black)\n![macOS](https://img.shields.io/badge/mac%20os-000000?style=for-the-badge\u0026logo=macos\u0026logoColor=F0F0F0)\n![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge\u0026logo=windows\u0026logoColor=white)\n\n\n\n**skimpy** is a light weight tool that provides summary statistics about variables in **pandas** or **Polars** data frames within the console or your interactive Python window.\n\nThink of it as a super-charged version of **pandas**' `df.describe()`.\n[You can find the documentation here](https://aeturrell.github.io/skimpy/).\n\n## Quickstart\n\n`skim` a **pandas** or **polars** dataframe and produce summary statistics within the console\nusing:\n\n```python\nfrom skimpy import skim\n\nskim(df)\n```\n\nwhere `df` is a **pandas** or **polars** dataframe.\n\nIf you need to a dataset to try *skimpy* out on, you can use the built-in test **Pandas** data frame:\n\n\n```python\nfrom skimpy import generate_test_data, skim\n\ndf = generate_test_data()\nskim(df)\n```\n\n\n\u003cpre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"\u003e╭──────────────────────────────────────────────── skimpy summary ─────────────────────────────────────────────────╮\n│ \u003cspan style=\"font-style: italic\"\u003e         Data Summary         \u003c/span\u003e \u003cspan style=\"font-style: italic\"\u003e      Data Types       \u003c/span\u003e \u003cspan style=\"font-style: italic\"\u003e       Categories        \u003c/span\u003e                                │\n│ ┏━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓ ┏━━━━━━━━━━━━━┳━━━━━━━┓ ┏━━━━━━━━━━━━━━━━━━━━━━━┓                                │\n│ ┃\u003cspan style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"\u003e Dataframe         \u003c/span\u003e┃\u003cspan style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"\u003e Values \u003c/span\u003e┃ ┃\u003cspan style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"\u003e Column Type \u003c/span\u003e┃\u003cspan style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"\u003e Count \u003c/span\u003e┃ ┃\u003cspan style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"\u003e Categorical Variables \u003c/span\u003e┃                                │\n│ ┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩ ┡━━━━━━━━━━━━━╇━━━━━━━┩ ┡━━━━━━━━━━━━━━━━━━━━━━━┩                                │\n│ │ Number of rows    │ 1000   │ │ float64     │ 3     │ │ class                 │                                │\n│ │ Number of columns │ 13     │ │ category    │ 2     │ │ location              │                                │\n│ └───────────────────┴────────┘ │ datetime64  │ 2     │ └───────────────────────┘                                │\n│                                │ object      │ 2     │                                                          │\n│                                │ int64       │ 1     │                                                          │\n│                                │ bool        │ 1     │                                                          │\n│                                │ string      │ 1     │                                                          │\n│                                │ timedelta64 │ 1     │                                                          │\n│                                └─────────────┴───────┘                                                          │\n│ \u003cspan style=\"font-style: italic\"\u003e                                                    number                                                    \u003c/span\u003e  │\n│ ┏━━━━━━━━━┳━━━━━━┳━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┳━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column  \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA   \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA %  \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e mean      \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e sd      \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e p0         \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e p25     \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e p50        \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e p75    \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e p100  \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e hist   \u003c/span\u003e┃  │\n│ ┡━━━━━━━━━╇━━━━━━╇━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━╇━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003elength \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e   0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e   0.5016\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e 0.3597\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e 1.573e-06\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e  0.134\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0.4976\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e0.8602\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    1\u003c/span\u003e │ \u003cspan style=\"color: #008000; text-decoration-color: #008000\"\u003e▇▃▃▃▅▇\u003c/span\u003e │  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003ewidth  \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e   0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    2.037\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e  1.929\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e  0.002057\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e  0.603\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e     1.468\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e 2.953\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e13.91\u003c/span\u003e │ \u003cspan style=\"color: #008000; text-decoration-color: #008000\"\u003e ▇▃▁  \u003c/span\u003e │  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003edepth  \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e   0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    10.02\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e  3.208\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e         2\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e      8\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e        10\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    12\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e   20\u003c/span\u003e │ \u003cspan style=\"color: #008000; text-decoration-color: #008000\"\u003e▁▃▇▆▃▁\u003c/span\u003e │  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003ernd    \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e 118\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e 11.8\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e -0.01977\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e  1.002\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    -2.809\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e-0.7355\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e-0.0007736\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e0.6639\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e3.717\u003c/span\u003e │ \u003cspan style=\"color: #008000; text-decoration-color: #008000\"\u003e▁▅▇▅▁ \u003c/span\u003e │  │\n│ └─────────┴──────┴───────┴───────────┴─────────┴────────────┴─────────┴────────────┴────────┴───────┴────────┘  │\n│ \u003cspan style=\"font-style: italic\"\u003e                                                   category                                                   \u003c/span\u003e  │\n│ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column                      \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA         \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA %            \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e ordered                 \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e unique              \u003c/span\u003e┃  │\n│ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eclass                      \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e         0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e              0\u003c/span\u003e │ \u003cspan style=\"color: #00d7ff; text-decoration-color: #00d7ff\"\u003eFalse                  \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e                  2\u003c/span\u003e │  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003elocation                   \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e         1\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e            0.1\u003c/span\u003e │ \u003cspan style=\"color: #00d7ff; text-decoration-color: #00d7ff\"\u003eFalse                  \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e                  5\u003c/span\u003e │  │\n│ └─────────────────────────────┴────────────┴─────────────────┴─────────────────────────┴─────────────────────┘  │\n│ \u003cspan style=\"font-style: italic\"\u003e                                                     bool                                                     \u003c/span\u003e  │\n│ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column                          \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e true             \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e true rate                      \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e hist                 \u003c/span\u003e┃  │\n│ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003ebooly_col                      \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e             516\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e                          0.52\u003c/span\u003e │ \u003cspan style=\"color: #008000; text-decoration-color: #008000\"\u003e       ▇    ▇       \u003c/span\u003e │  │\n│ └─────────────────────────────────┴──────────────────┴────────────────────────────────┴──────────────────────┘  │\n│ \u003cspan style=\"font-style: italic\"\u003e                                                   datetime                                                   \u003c/span\u003e  │\n│ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column                       \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA    \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA %     \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e first              \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e last              \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e frequency       \u003c/span\u003e┃  │\n│ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003edatetime                    \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e       0\u003c/span\u003e │ \u003cspan style=\"color: #800000; text-decoration-color: #800000\"\u003e    2018-01-31    \u003c/span\u003e │ \u003cspan style=\"color: #800000; text-decoration-color: #800000\"\u003e   2101-04-30    \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eME             \u003c/span\u003e │  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003edatetime_no_freq            \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    3\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e     0.3\u003c/span\u003e │ \u003cspan style=\"color: #800000; text-decoration-color: #800000\"\u003e    1992-01-05    \u003c/span\u003e │ \u003cspan style=\"color: #800000; text-decoration-color: #800000\"\u003e   2023-03-04    \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eNone           \u003c/span\u003e │  │\n│ └──────────────────────────────┴───────┴──────────┴────────────────────┴───────────────────┴─────────────────┘  │\n│ \u003cspan style=\"font-style: italic\"\u003e                                           \u0026lt;class 'datetime.date'\u0026gt;                                            \u003c/span\u003e  │\n│ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column                           \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA    \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA %     \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e first            \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e last             \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e frequency      \u003c/span\u003e┃  │\n│ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003edatetime.date                   \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e       0\u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003e2018-01-31      \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003e2101-04-30      \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eME            \u003c/span\u003e │  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003edatetime.date_no_freq           \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e       0\u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003e1992-01-05      \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003e2023-03-04      \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eNone          \u003c/span\u003e │  │\n│ └──────────────────────────────────┴───────┴──────────┴──────────────────┴──────────────────┴────────────────┘  │\n│ \u003cspan style=\"font-style: italic\"\u003e                                                 timedelta64                                                  \u003c/span\u003e  │\n│ ┏━━━━━━━━━━━━━━━━┳━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column         \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA   \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA %    \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e mean                   \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e median                 \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e max                    \u003c/span\u003e┃  │\n│ ┡━━━━━━━━━━━━━━━━╇━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003etime diff     \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e   5\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e    0.5\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e       8 days 00:05:47\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e       0 days 00:00:00\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e      26 days 00:00:00\u003c/span\u003e │  │\n│ └────────────────┴──────┴─────────┴────────────────────────┴────────────────────────┴────────────────────────┘  │\n│ \u003cspan style=\"font-style: italic\"\u003e                                                    string                                                    \u003c/span\u003e  │\n│ ┏━━━━━━━━┳━━━━┳━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e        \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e    \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e      \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e            \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e           \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e            \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e           \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e chars per  \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e words per \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e total      \u003c/span\u003e┃  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA % \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e shortest   \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e longest   \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e min        \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e max       \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e row        \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e row       \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e words      \u003c/span\u003e┃  │\n│ ┡━━━━━━━━╇━━━━╇━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003etext  \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e 6\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e 0.6\u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eHow are   \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eIndeed,  \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eHow are   \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eWhat     \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e      31.1\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e      5.8\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e      5761\u003c/span\u003e │  │\n│ │        │    │      │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eyou?      \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eit was   \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eyou?      \u003c/span\u003e │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eweather! \u003c/span\u003e │            │           │            │  │\n│ │        │    │      │            │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003ethe most \u003c/span\u003e │            │           │            │           │            │  │\n│ │        │    │      │            │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eoutrageou\u003c/span\u003e │            │           │            │           │            │  │\n│ │        │    │      │            │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003esly      \u003c/span\u003e │            │           │            │           │            │  │\n│ │        │    │      │            │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003epompous  \u003c/span\u003e │            │           │            │           │            │  │\n│ │        │    │      │            │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003ecat I    \u003c/span\u003e │            │           │            │           │            │  │\n│ │        │    │      │            │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003ehave ever\u003c/span\u003e │            │           │            │           │            │  │\n│ │        │    │      │            │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003eseen.    \u003c/span\u003e │            │           │            │           │            │  │\n│ └────────┴────┴──────┴────────────┴───────────┴────────────┴───────────┴────────────┴───────────┴────────────┘  │\n│ \u003cspan style=\"font-style: italic\"\u003e                                                    object                                                    \u003c/span\u003e  │\n│ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓  │\n│ ┃\u003cspan style=\"font-weight: bold\"\u003e column                                                                  \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA           \u003c/span\u003e┃\u003cspan style=\"font-weight: bold\"\u003e NA %              \u003c/span\u003e┃  │\n│ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003edatetime.date                                                          \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e           0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e                0\u003c/span\u003e │  │\n│ │ \u003cspan style=\"color: #af87ff; text-decoration-color: #af87ff\"\u003edatetime.date_no_freq                                                  \u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e           0\u003c/span\u003e │ \u003cspan style=\"color: #008080; text-decoration-color: #008080\"\u003e                0\u003c/span\u003e │  │\n│ └─────────────────────────────────────────────────────────────────────────┴──────────────┴───────────────────┘  │\n╰────────────────────────────────────────────────────── End ──────────────────────────────────────────────────────╯\n\u003c/pre\u003e\n\n\n\nIt is recommended that you set your datatypes before using **skimpy** (for example converting any text columns to pandas string datatype), as this will produce richer statistical summaries. However, the `skim()` function will try and guess what the datatypes of your columns are.\n\n## Requirements\n\nYou can find a full list of requirements in the [pyproject.toml](https://github.com/aeturrell/skimpy/blob/main/pyproject.toml) file.\n\nYou can try this package out right now in your browser using this\n[Google Colab notebook](https://colab.research.google.com/gist/aeturrell/7bf183c559dc1d15ab7e7aaac39ea0ed/skimpy_demo.ipynb)\n(requires a Google account). Note that the Google Colab notebook uses the latest package released on PyPI (rather than the development release).\n\n## Installation\n\nYou can install the latest release of *skimpy* via\n[pip](https://pip.pypa.io/) from [PyPI](https://pypi.org/):\n\n```bash\n$ pip install skimpy\n```\n\nTo install the development version from git, use:\n\n```bash\n$ pip install git+https://github.com/aeturrell/skimpy.git\n```\n\nFor development, see [contributing](contributing.qmd).\n\n## License\n\nDistributed under the terms of the [MIT license](https://opensource.org/licenses/MIT), *skimpy* is free and open source software.\n\n## Issues\n\nIf you encounter any problems, please [file an issue](https://github.com/aeturrell/skimpy/issues) along with a detailed description.\n\n## Credits\n\nThis project was generated from [\\@cjolowicz](https://github.com/cjolowicz)\\'s [Hypermodern Python Cookiecutter](https://github.com/cjolowicz/cookiecutter-hypermodern-python) template.\n\n**skimpy** was inspired by the R package [**skimr**](https://docs.ropensci.org/skimr/articles/skimr.html) and by exploratory Python packages including [**ydata_profiling**](https://docs.profiling.ydata.ai) and [**dataprep**](https://dataprep.ai/), from which the `clean_columns` function comes.\n\nThis package would not have been possible without the [**Rich**](https://github.com/Textualize/rich) package.\n\nThe package is built with [poetry](https://python-poetry.org/), while the documentation is built with [Quarto](https://quarto.org/) and [Quartodoc](https://github.com/machow/quartodoc) (a Python package). Tests are run with [nox](https://nox.thea.codes/en/stable/).\n\nUsing **skimpy** in your paper? Let us know by raising an issue beginning with \"citation\" and we'll add it to this page.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faeturrell%2Fskimpy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faeturrell%2Fskimpy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faeturrell%2Fskimpy/lists"}