Skip to main content

advertools visualizations

Project description

adviz

Get startd quickly and see exmaples below

Install

pip install adviz

How to use

Count unique values in a list of items

value_counts_plus(list('aaaaaaaaabbbbcccddddddddddeeeeeeeeeeeeffffggghhhiijjjjkkkllllmmmmmmmnnooop'))
<style type="text/css"> #T_712df_row0_col1, #T_712df_row0_col3 { background-color: #cebc63; color: #000000; } #T_712df_row0_col2, #T_712df_row0_col4, #T_712df_row8_col1, #T_712df_row8_col3, #T_712df_row9_col1, #T_712df_row9_col3 { background-color: #00224e; color: #f1f1f1; } #T_712df_row1_col1, #T_712df_row1_col3 { background-color: #9d9576; color: #f1f1f1; } #T_712df_row1_col2, #T_712df_row1_col4 { background-color: #293f6e; color: #f1f1f1; } #T_712df_row2_col1, #T_712df_row2_col3 { background-color: #878478; color: #f1f1f1; } #T_712df_row2_col2, #T_712df_row2_col4 { background-color: #51586d; color: #f1f1f1; } #T_712df_row3_col1, #T_712df_row3_col3 { background-color: #5e636f; color: #f1f1f1; } #T_712df_row3_col2, #T_712df_row3_col4 { background-color: #6b6d72; color: #f1f1f1; } #T_712df_row4_col1, #T_712df_row4_col3, #T_712df_row5_col1, #T_712df_row5_col3, #T_712df_row6_col1, #T_712df_row6_col3, #T_712df_row7_col1, #T_712df_row7_col3 { background-color: #013271; color: #f1f1f1; } #T_712df_row4_col2, #T_712df_row4_col4 { background-color: #787877; color: #f1f1f1; } #T_712df_row5_col2, #T_712df_row5_col4 { background-color: #888578; color: #f1f1f1; } #T_712df_row6_col2, #T_712df_row6_col4 { background-color: #979177; color: #f1f1f1; } #T_712df_row7_col2, #T_712df_row7_col4 { background-color: #a89e73; color: #f1f1f1; } #T_712df_row8_col2, #T_712df_row8_col4 { background-color: #b5a86f; color: #f1f1f1; } #T_712df_row9_col2, #T_712df_row9_col4 { background-color: #c2b369; color: #000000; } #T_712df_row10_col1, #T_712df_row10_col2, #T_712df_row10_col3, #T_712df_row10_col4 { background-color: #fee838; color: #000000; } </style>

Counts of data

  data count cum_count perc cum_perc
0 e 12 12 16.2% 16.2%
1 d 10 22 13.5% 29.7%
2 a 9 31 12.2% 41.9%
3 m 7 38 9.5% 51.4%
4 b 4 42 5.4% 56.8%
5 f 4 46 5.4% 62.2%
6 j 4 50 5.4% 67.6%
7 l 4 54 5.4% 73.0%
8 c 3 57 4.1% 77.0%
9 g 3 60 4.1% 81.1%
10 Others: 14 74 18.9% 100.0%

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

adviz-0.0.1.tar.gz (9.9 kB view details)

Uploaded Source

Built Distribution

adviz-0.0.1-py3-none-any.whl (8.9 kB view details)

Uploaded Python 3

File details

Details for the file adviz-0.0.1.tar.gz.

File metadata

  • Download URL: adviz-0.0.1.tar.gz
  • Upload date:
  • Size: 9.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.1

File hashes

Hashes for adviz-0.0.1.tar.gz
Algorithm Hash digest
SHA256 961eabc8ec6022d47a41a0f7cd4f4ed696571540783617763a3cead355ef17cd
MD5 533bf3d7a54b5251f6e7814eac9a68da
BLAKE2b-256 19150899dd06e0ba99804c56030f287d5bd7d648bcfc4403937822d4d962dddb

See more details on using hashes here.

Provenance

File details

Details for the file adviz-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: adviz-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 8.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.1

File hashes

Hashes for adviz-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9dd4c396a3caa67a2846e339fdf637c1b0892b9196452af84a70cf316636ba1c
MD5 b86544951d4306586e51fc24509ea817
BLAKE2b-256 061ffa7dbaefe76489154bd3ca1f2060c73870aad0100661f3027519b4a4dbe7

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page