Saved evidence report
Explore the saved analysis below. Controls filter this report; they do not rerun the analysis or retrieve source data.
Population: input · 8 evaluated source rows
Analysis: 8 rows; presence=per_row
Search limits restrict what was tested or retained. Untested work is unknown. Display limits below only restrict this report.
missingness: 3/3 pairs evaluated
missingness: 4/4 signatures retained
| pair candidates | 3 |
|---|---|
| pairs evaluated | 3 |
| signatures total | 4 |
| signatures shown | 4 |
| signature omitted units | 0 |
| signature omitted rows | 0 |
| contexts total | 0 |
| contexts shown | 0 |
| entity missing key rows | 0 |
The visual summary has its own display limit of up to 12 items per list. Browse the included evidence below.
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Analysis: rows; presence=per_row
Finding f0 · counting unit: rows
| populated | 6 |
|---|---|
| missing | 2 |
| denominator | 8 |
| populated fraction | 0.75 |
Positions are zero-based offsets in the original ordered source, not dataframe index labels. Saved samples are the first matches in source order; their size is not the total support.
Examples: 5/6 saved source positions [0, 1, 3, 4, 5]
Exceptions: 2/2 saved source positions [2, 7]
In Python, with this result named result and its identical ordered source named df:
result.inspect(df, 'f0')
Use all_matches=True to retrieve all matching rows and exceptions=True for exception rows. These operations require the original source and a Python session.
| presence | some |
|---|
Analysis: rows; presence=per_row
Finding f1 · counting unit: rows
| populated | 5 |
|---|---|
| missing | 3 |
| denominator | 8 |
| populated fraction | 0.625 |
Positions are zero-based offsets in the original ordered source, not dataframe index labels. Saved samples are the first matches in source order; their size is not the total support.
Examples: 5/5 saved source positions [0, 1, 2, 5, 6]
Exceptions: 3/3 saved source positions [3, 4, 7]
In Python, with this result named result and its identical ordered source named df:
result.inspect(df, 'f1')
Use all_matches=True to retrieve all matching rows and exceptions=True for exception rows. These operations require the original source and a Python session.
| presence | some |
|---|
Analysis: rows; presence=per_row
Finding f2 · counting unit: rows
| count | 4 |
|---|---|
| denominator | 8 |
Positions are zero-based offsets in the original ordered source, not dataframe index labels. Saved samples are the first matches in source order; their size is not the total support.
Examples: 4/4 saved source positions [0, 1, 5, 6]
Exceptions: 0/0 saved source positions []
In Python, with this result named result and its identical ordered source named df:
result.inspect(df, 'f2')
Use all_matches=True to retrieve all matching rows and exceptions=True for exception rows. These operations require the original source and a Python session.
| present | crop, tray, pickup_day |
|---|---|
| absent | none |
Analysis: rows; presence=per_row
Finding f3 · counting unit: rows
| count | 2 |
|---|---|
| denominator | 8 |
Positions are zero-based offsets in the original ordered source, not dataframe index labels. Saved samples are the first matches in source order; their size is not the total support.
Examples: 2/2 saved source positions [3, 4]
Exceptions: 0/0 saved source positions []
In Python, with this result named result and its identical ordered source named df:
result.inspect(df, 'f3')
Use all_matches=True to retrieve all matching rows and exceptions=True for exception rows. These operations require the original source and a Python session.
| present | crop, tray |
|---|---|
| absent | pickup_day |
Analysis: rows; presence=per_row
Finding f4 · counting unit: rows
| count | 1 |
|---|---|
| denominator | 8 |
Positions are zero-based offsets in the original ordered source, not dataframe index labels. Saved samples are the first matches in source order; their size is not the total support.
Examples: 1/1 saved source positions [7]
Exceptions: 0/0 saved source positions []
In Python, with this result named result and its identical ordered source named df:
result.inspect(df, 'f4')
Use all_matches=True to retrieve all matching rows and exceptions=True for exception rows. These operations require the original source and a Python session.
| present | crop |
|---|---|
| absent | tray, pickup_day |
Analysis: rows; presence=per_row
Finding f5 · counting unit: rows
| count | 1 |
|---|---|
| denominator | 8 |
Positions are zero-based offsets in the original ordered source, not dataframe index labels. Saved samples are the first matches in source order; their size is not the total support.
Examples: 1/1 saved source positions [2]
Exceptions: 0/0 saved source positions []
In Python, with this result named result and its identical ordered source named df:
result.inspect(df, 'f5')
Use all_matches=True to retrieve all matching rows and exceptions=True for exception rows. These operations require the original source and a Python session.
| present | crop, pickup_day |
|---|---|
| absent | tray |