Here's an example Validation Result (not from your data) in JSON format. This object has rich context about the test failure.
Validation results save you time.
This is an example of what a single failed Expectation looks like in Data Docs. Note the failure includes unexpected values from your data. This helps you debug pipelines faster.
Great Expectations provides a large library of expectations.
Nearly 50 built in expectations allow you to express how you understand your data, and you can add custom
expectations if you need a new one.
Now explore and edit the sample suite!
This sample suite shows you a few examples of expectations.
Note this is not a production suite and was generated using only a small sample of your data.
When you are ready, press the How to Edit button to kick off the iterative dev loop.
How to Edit This Expectation Suite
Expectations are best edited interactively in Jupyter notebooks.
To automatically generate a notebook that does this run:
Once you have made your changes and run the entire notebook you can kill the notebook by pressing Ctr-C in your terminal.
Because these notebooks are generated from an Expectation Suite, these notebooks are entirely disposable.
Expectation Suite
A collection of Expectations defined for batches of data.
Must have these columns in this order: Unnamed: 0, Daily Time Spent on Site, Age, Area Income, Daily Internet Usage, Ad Topic Line, City, Male, Country, Timestamp, Clicked on Ad
Notes
This Expectation suite currently contains 38 total Expectations across 10 columns.
Ad Topic Line
values must never be null.
value types must belong to this set: CHARNCHARVARCHARNVARCHARTEXTNTEXTSTRINGStringTypestringstrobjectdtype('O').
Age
minimum value must be greater than or equal to 15 and less than or equal to 23.
maximum value must be greater than or equal to 57 and less than or equal to 70.
mean must be greater than or equal to 30 and less than or equal to 40.
values must never be null.
value types must belong to this set: INTEGERintegerintint_int8int16int32int64uint8uint16uint32uint64INTINTEGERINT64TINYINTBYTEINTSMALLINTBIGINTIntegerTypeLongType.
Area Income
minimum value must be greater than or equal to 12000 and less than or equal to 15000.
maximum value must be greater than or equal to 70000 and less than or equal to 80000.
mean must be greater than or equal to 54000 and less than or equal to 65000.
values must never be null.
value types must belong to this set: FLOATFLOAT4FLOAT8FLOAT64DOUBLEDOUBLE_PRECISIONNUMERICFloatTypeDoubleTypefloat_float16float32float64numberDECIMALREAL.
City
values must never be null.
fraction of unique values must be greater than or equal to 0.9 and less than or equal to 0.999.
value types must belong to this set: CHARNCHARVARCHARNVARCHARTEXTNTEXTSTRINGStringTypestringstrobjectdtype('O').
Clicked on Ad
mean must be greater than or equal to 0.45 and less than or equal to 0.55.
values must belong to this set: 01.
values must never be null.
value types must belong to this set: INTEGERintegerintint_int8int16int32int64uint8uint16uint32uint64INTINTEGERINT64TINYINTBYTEINTSMALLINTBIGINTIntegerTypeLongType.
Country
values must never be null.
value types must belong to this set: CHARNCHARVARCHARNVARCHARTEXTNTEXTSTRINGStringTypestringstrobjectdtype('O').
Daily Internet Usage
minimum value must be greater than or equal to 95 and less than or equal to 110.
maximum value must be greater than or equal to 250 and less than or equal to 270.
mean must be greater than or equal to 170 and less than or equal to 185.
values must never be null.
value types must belong to this set: FLOATFLOAT4FLOAT8FLOAT64DOUBLEDOUBLE_PRECISIONNUMERICFloatTypeDoubleTypefloat_float16float32float64numberDECIMALREAL.
Daily Time Spent on Site
minimum value must be greater than or equal to 30 and less than or equal to 40.
maximum value must be greater than or equal to 85 and less than or equal to 100.
mean must be greater than or equal to 55 and less than or equal to 70.
values must never be null.
value types must belong to this set: FLOATFLOAT4FLOAT8FLOAT64DOUBLEDOUBLE_PRECISIONNUMERICFloatTypeDoubleTypefloat_float16float32float64numberDECIMALREAL.
Male
values must belong to this set: 01.
mean must be greater than or equal to 0.45 and less than or equal to 0.55.
values must never be null.
value types must belong to this set: INTEGERintegerintint_int8int16int32int64uint8uint16uint32uint64INTINTEGERINT64TINYINTBYTEINTSMALLINTBIGINTIntegerTypeLongType.
Timestamp
values must never be null.
value types must belong to this set: CHARNCHARVARCHARNVARCHARTEXTNTEXTSTRINGStringTypestringstrobjectdtype('O').