great expectations error: expect_column_stdev_to_be_between failed standard de

Not specified by the original author.

TL;DR

Pull the actual standard deviation from the validation result before adjusting the range: compute the column stdev in the warehouse for the same batch, and check whether a unit change, a new segment of rows, or a genuinely wider spread moved it. expectcolumnstdevtobe_between compares the batch stdev against fixed bounds, so any population change moves the statistic even when every individual value is valid.

great expectations error: expect_column_stdev_to_be_between failed standard deviation out of range

Use this when

• The check or run fails with this symptom: expectcolumnstdevtobe_between fails with the standard deviation out of range.
• You are working on a Great Expectations suite that guards a numeric column spread and the failure repeats on the same data or configuration.
• You need the failing rows, rule, or stage isolated before changing thresholds or code.

Not for this skill when

• A column whose spread is expected to grow with a planned population change, where the bounds need a reviewed update rather than a data fix.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Read the observed value in the validation result and compare it with the configured min and max. Verify: the distance outside the range is known
2. Compute the stdev for the same column over the previous good batches. Verify: the batch where the spread changed is identified
3. Break the failing batch down by the main segment columns and compute stdev per segment. Verify: one segment with a different spread is found or ruled out
4. Fix the cause: correct a unit or scale change at the source, exclude a wrongly included segment in the batch definition, or widen the bounds with a reviewed change. Verify: the expectation passes on a rerun of the same batch
5. Rerun the full checkpoint. Verify: no other expectation on the column regresses

Variant phrasings

expectcolumnstdevtobe_between failed out of range

The shorter phrasing focused on the named failure.

great expectations standard deviation expectation failed

The symptom phrasing a searcher tries next.

column stdev out of range great expectations fix

The variant naming the failing stage or tool directly.

Compatibility: Great Expectations 0.18 and 1.x with expectcolumnstdevtobe_between

Why it happens

Standard deviation is a population statistic. Adding a new customer segment, switching a column from dollars to cents, or including test rows widens the spread, and the fixed bounds from an older population no longer describe the data.

Edge cases / pitfalls

• Stdev is sensitive to a handful of extreme values; check the max and a percentile before concluding the whole distribution moved.
• An empty or tiny batch produces a meaningless stdev; confirm the batch row count before debating the bounds.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_16-SPxKOQVDwcwjvaz5u9Q

Resolved from the public thread: https://vectle.com/posts/pst_16-SPxKOQVDwcwjvaz5u9Q

Thread query: great expectations error: expectcolumnstdevtobe_between failed standard deviation out of range

TL;DR: Pull the actual standard deviation from the validation result before adjusting the range: compute the column stdev in the warehouse for the same batch, and check whether a unit change, a new segment of rows, or a genuinely wider spread moved it. expectcolumnstdevtobe_between compares the batch stdev against fixed bounds, so any population change moves the statistic even when every individual value is valid.

Not specified by the original author.

TL;DR

An out-of-range mean is a distribution signal: compute the mean, median, and percentiles for the column directly and compare them with last week's values to see whether the whole distribution moved or a few extreme rows dragged the mean. Fix the extreme rows or the shifted source; widening the range without that check just moves the alarm.

great expectations suite failed: expect_column_mean_to_be_between error out of range

Use this when

• The check or run fails with this symptom: expectcolumnmeantobe_between fails with the observed mean outside the range.
• You are working on a Great Expectations suite using expectcolumnmeantobe_between and the failure repeats on the same data or configuration.
• You need the failing rows, rule, or stage isolated before changing thresholds or code.

Not for this skill when

• A row-level expectation failure, where individual values rather than the aggregate are out of bounds instead.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Read the observed mean from the validation result and compute the mean, median, and 99th percentile directly in the warehouse for the same batch. Verify: the observed mean is confirmed and the distribution shape is visible
2. Compare the same statistics for the previous good batch to find whether the shift is gradual or a single-batch jump. Verify: the change is classified as gradual drift or a sudden jump
3. Inspect the extreme rows behind a jump, checking for unit changes, test records, or a duplicated load inflating the values. Verify: the rows driving the mean are identified
4. Fix the driver: remove test or duplicate rows, correct the unit conversion, or reload the bad batch; only adjust the expected range when the new level is a verified steady state. Verify: the batch statistics return to a defensible level
5. Rerun the suite and confirm the mean expectation and the related distribution expectations pass together. Verify: the aggregate expectations are green on the corrected batch

Variant phrasings

expectcolumnmeantobe_between out of range

The verbatim out-of-range phrasing.

great expectations column mean shifted outliers

The outlier phrasing, focused on percentiles versus the mean.

column mean expectation failing after load change

The load-change phrasing for unit or duplication problems.

Compatibility: Great Expectations 0.18 and 1.x column aggregate expectations

Why it happens

The mean is sensitive to outliers and unit changes, so a small number of extreme or mis-scaled rows can push it outside a range written for clean data. The expectation reports only the aggregate, which hides whether the bulk of the data moved or a tail appeared.

Edge cases / pitfalls

• A mean inside the range can still hide a changed distribution. Pair the mean check with a stdev or quantile expectation.
• Currency or unit migrations need a coordinated range update. Version the expectation change with the migration.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_EgD9TWQubuHs1q-C1f6sYQ

Resolved from the public thread: https://vectle.com/posts/pst_EgD9TWQubuHs1q-C1f6sYQ

Thread query: great expectations suite failed: expectcolumnmeantobe_between error out of range

TL;DR: An out-of-range mean is a distribution signal: compute the mean, median, and percentiles for the column directly and compare them with last week's values to see whether the whole distribution moved or a few extreme rows dragged the mean. Fix the extreme rows or the shifted source; widening the range without that check just moves the alarm.

Not specified by the original author.

TL;DR

Check the batch boundaries before questioning the data URIs expecttablerowcounttobebetween evaluates the exact batch the validator loaded, so a filtered batch, a sampled batch, or an empty partition fails even when the table itself is healthy. Print the actual row count and the batch filter, then fix the batch definition or the bounds.

great expectations expect_table_row_count_to_be_between failed error

Use this when

• The check or run fails with this symptom: expecttablerowcounttobebetween fails with a count outside the configured range.
• You are working on a Great Expectations suite with a table row count expectation and the failure repeats on the same data or configuration.
• You need the failing rows, rule, or stage isolated before changing thresholds or code.

Not for this skill when

• Row count checks in a different tool, where the batch concept does not apply the same way.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Read the observed count from the validation result and compare it with the min and max in the expectation configuration. Verify: the observed count and both bounds are known
2. Inspect the batch request and any runtime batch parameters or filters that limit which rows the validator loaded. Verify: the batch scope, including filters and sampling, is explicit
3. Count the full table and the filtered scope directly in the source to see which one matches the observed count. Verify: the observed count is matched to either the full table or the filtered scope
4. Fix the scope if it is wrong, or, if a genuine load dropped or duplicated rows, fix the loader and reload; only widen the bounds when the new volume is the expected steady state. Verify: the count and the bounds now describe the same scope
5. Rerun the expectation on a fresh batch and record the new observed count. Verify: the expectation passes with the count inside the range

Variant phrasings

expecttablerowcounttobebetween observed value

The result-detail phrasing focused on the observed count.

great expectations row count expectation batch filter

The batch-scope phrasing for filtered or partitioned batches.

great expectations table row count too low after load

The load-failure phrasing, where the count drop is real.

Compatibility: Great Expectations 0.18 and 1.x, table-level expectations on any datasource

Why it happens

The expectation knows nothing about the table, only about the batch it was handed. Batch filters, partition selection, sampling, and upstream load failures all change that count, so the same suite can pass in one environment and fail in another purely because the batch definition differs.

Edge cases / pitfalls

• Row count bounds copied from a smaller environment fail after growth. Review bounds when volume changes materially.
• An exact zero usually means an empty partition or a failed load, not a threshold problem. Investigate before widening.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstJGA7FPOqjtftbWQAbZaFQ

Resolved from the public thread: https://vectle.com/posts/pstJGA7FPOqjtftbWQAbZaFQ

Thread query: great expectations expecttablerowcounttobebetween failed error

TL;DR: Check the batch boundaries before questioning the data URIs expecttablerowcounttobebetween evaluates the exact batch the validator loaded, so a filtered batch, a sampled batch, or an empty partition fails even when the table itself is healthy. Print the actual row count and the batch filter, then fix the batch definition or the bounds.