Special CharactersΒΆ
[1]:
from deepchecks.checks import SpecialCharacters
import pandas as pd
[2]:
data = {'col1': [' ', '!', '"', '#', '$', '%', '&', '\'','(', ')',
'*', '+', ',', '-', '.', '/', ':', ';', '<', '=',
'>', '?', '@', '[', ']', '\\', '^', '_', '`', '{',
'}', '|', '~', '\n'],
'col2':['v', 'v', 'v', 'v4', 'v5', 'v6', 'v7', 'v8','v9','v10',
'*', '+', ',', '-', '.', '/', ':', ';', '<', '=',
'>', '?', '@', '[', ']', '\\', '^', '_', '`', '{',
'}', '|', '~', '\n'],
'col3': [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,11,1,'???#',1,1,1,1,1,1,1,1,1,1,1],
'col4': [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,11,1,1,1,1,1,1,1,1,1,1,1,1,1],
'col5': ['valid1','valid2','valid3','valid4','valid5','valid6','valid7',
'valid8','valid9','valid10','valid11','valid12',
'valid13','valid14','inval!d15','valid16','valid17','valid18',
'valid19','valid20','valid21','valid22','valid23','valid24','valid25',
'valid26', 'valid27','valid28','valid29','valid30','valid31','32','33','34']}
dataframe = pd.DataFrame(data=data)
SpecialCharacters().run(dataframe)
Special Characters
Search in column[s] for values that contains only special characters. Read More...
Additional Outputs
* showing only the top 10 columns, you can change it using n_top_columns param
| % Special-Only Samples | Most Common Special-Only Samples | |
|---|---|---|
| Column Name | ||
| col1 | 100% | [' ', '!'] |
| col2 | 70.59% | ['*', '+'] |
| col3 | 2.94% | ['???#'] |
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