Overview

Dataset statistics

Number of variables4
Number of observations2
Missing cells0
Missing cells (%)0.0%
Total size in memory192.0 B
Average record size in memory96.0 B

Variable types

Categorical4

Alerts

eligible_processes_for_digitalization has constant value "4169" Constant
fiscal_year is uniformly distributed Uniform
completed_digitalized_processes is uniformly distributed Uniform
digitalization_rate is uniformly distributed Uniform
fiscal_year has unique values Unique
completed_digitalized_processes has unique values Unique
digitalization_rate has unique values Unique

Reproduction

Analysis started2026-04-13 10:07:15.294687
Analysis finished2026-04-13 10:07:15.794854
Duration0.5 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

fiscal_year
Categorical

UNIFORM
UNIQUE

Distinct2
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size144.0 B
2567
2568

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2567
2nd row2568

Common Values

ValueCountFrequency (%)
25671
50.0%
25681
50.0%

Length

2026-04-13T17:07:15.895658image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-04-13T17:07:15.989270image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
25681
50.0%
25671
50.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

completed_digitalized_processes
Categorical

UNIFORM
UNIQUE

Distinct2
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size144.0 B
3491
2701

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2701
2nd row3491

Common Values

ValueCountFrequency (%)
34911
50.0%
27011
50.0%

Length

2026-04-13T17:07:16.085980image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-04-13T17:07:16.183069image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
27011
50.0%
34911
50.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

eligible_processes_for_digitalization
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size144.0 B
4169

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4169
2nd row4169

Common Values

ValueCountFrequency (%)
41692
100.0%

Length

2026-04-13T17:07:16.279979image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-04-13T17:07:16.370795image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
41692
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

digitalization_rate
Categorical

UNIFORM
UNIQUE

Distinct2
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size144.0 B
0.6479
0.8374

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row0.6479
2nd row0.8374

Common Values

ValueCountFrequency (%)
0.64791
50.0%
0.83741
50.0%

Length

2026-04-13T17:07:16.459165image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-04-13T17:07:16.551470image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
0.83741
50.0%
0.64791
50.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Sample

First rows

fiscal_yearcompleted_digitalized_processeseligible_processes_for_digitalizationdigitalization_rate
02567270141690.6479
12568349141690.8374

Last rows

fiscal_yearcompleted_digitalized_processeseligible_processes_for_digitalizationdigitalization_rate
02567270141690.6479
12568349141690.8374