Overview

Dataset statistics

Number of variables6
Number of observations2150
Missing cells0
Missing cells (%)0.0%
Total size in memory100.9 KiB
Average record size in memory48.1 B

Variable types

Categorical5
Numeric1

Alerts

Year has constant value "2024" Constant
EconomyName has a high cardinality: 55 distinct values High cardinality
EconomyCode is uniformly distributed Uniform
Pillar & Topic is uniformly distributed Uniform

Reproduction

Analysis started2025-12-14 10:07:50.342439
Analysis finished2025-12-14 10:07:50.561498
Duration0.22 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

EconomyName
Categorical

HIGH CARDINALITY

Distinct55
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
Bangladesh
 
43
Mauritius
 
43
Romania
 
43
El Salvador
 
43
Indonesia
 
43
Other values (50)
1935 

Length

Max length24
Median length8
Mean length9.354883721
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 rowSingapore
2nd rowSingapore
3rd rowSingapore
4th rowEstonia
5th rowEstonia

Common Values

ValueCountFrequency (%)
Bangladesh43
 
2.0%
Mauritius43
 
2.0%
Romania43
 
2.0%
El Salvador43
 
2.0%
Indonesia43
 
2.0%
Seychelles43
 
2.0%
Montenegro43
 
2.0%
Estonia43
 
2.0%
Peru43
 
2.0%
Croatia43
 
2.0%
Other values (45)1720
80.0%

Length

2025-12-14T17:07:50.678136image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
republic129
 
4.3%
and86
 
2.9%
togo43
 
1.4%
morocco43
 
1.4%
timor-leste43
 
1.4%
new43
 
1.4%
zealand43
 
1.4%
slovak43
 
1.4%
ghana43
 
1.4%
vanuatu43
 
1.4%
Other values (60)2415
81.2%

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

EconomyCode
Categorical

UNIFORM

Distinct50
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
MDG
 
43
MAR
 
43
TCD
 
43
RWA
 
43
BIH
 
43
Other values (45)
1935 

Length

Max length3
Median length3
Mean length3
Min length3

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 rowSGP
2nd rowSGP
3rd rowSGP
4th rowEST
5th rowEST

Common Values

ValueCountFrequency (%)
MDG43
 
2.0%
MAR43
 
2.0%
TCD43
 
2.0%
RWA43
 
2.0%
BIH43
 
2.0%
SLV43
 
2.0%
KHM43
 
2.0%
PER43
 
2.0%
BRB43
 
2.0%
IDN43
 
2.0%
Other values (40)1720
80.0%

Length

2025-12-14T17:07:50.849918image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
bwa43
 
2.0%
hrv43
 
2.0%
gmb43
 
2.0%
bgr43
 
2.0%
vut43
 
2.0%
pry43
 
2.0%
tza43
 
2.0%
syc43
 
2.0%
prt43
 
2.0%
vnm43
 
2.0%
Other values (40)1720
80.0%

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

Year
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
2024
2150 

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 row2024
2nd row2024
3rd row2024
4th row2024
5th row2024

Common Values

ValueCountFrequency (%)
20242150
100.0%

Length

2025-12-14T17:07:50.974148image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2025-12-14T17:07:51.055875image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
20242150
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

Main
Categorical

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
Taxation
200 
Business Insolvency
200 
Business Location
200 
International Trade
200 
Dispute Resolution
200 
Other values (6)
1150 

Length

Max length19
Median length17
Mean length14.62790698
Min length5

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 rowOverall
2nd rowOverall
3rd rowOverall
4th rowOverall
5th rowOverall

Common Values

ValueCountFrequency (%)
Taxation200
9.3%
Business Insolvency200
9.3%
Business Location200
9.3%
International Trade200
9.3%
Dispute Resolution200
9.3%
Financial Services200
9.3%
Business Entry200
9.3%
Market Competition200
9.3%
Utility Services200
9.3%
Labor200
9.3%

Length

2025-12-14T17:07:51.147127image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
business600
16.0%
services400
 
10.7%
labor200
 
5.3%
utility200
 
5.3%
competition200
 
5.3%
market200
 
5.3%
entry200
 
5.3%
financial200
 
5.3%
resolution200
 
5.3%
dispute200
 
5.3%
Other values (6)1150
30.7%

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

Pillar & Topic
Categorical

UNIFORM

Distinct43
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
Pillar I: Quality of Regulations on Taxation
 
50
Pillar III: Operational Efficiency of Labor Regulations and Public Services in Practice
 
50
Pillar III: Operational Efficiency of Resolving Judicial Insolvency Proceedings
 
50
Labor Overall
 
50
Pillar I: Quality of Regulations that Promote Market Competition
 
50
Other values (38)
1900 

Length

Max length102
Median length54
Mean length52.30232558
Min length13

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 rowPillar 1 Regulatory Framework
2nd rowPillar 2 Public Services
3rd rowPillar 3 Operational Efficiency
4th rowPillar 1 Regulatory Framework
5th rowPillar 2 Public Services

Common Values

ValueCountFrequency (%)
Pillar I: Quality of Regulations on Taxation50
 
2.3%
Pillar III: Operational Efficiency of Labor Regulations and Public Services in Practice50
 
2.3%
Pillar III: Operational Efficiency of Resolving Judicial Insolvency Proceedings50
 
2.3%
Labor Overall50
 
2.3%
Pillar I: Quality of Regulations that Promote Market Competition50
 
2.3%
Pillar I: Quality of Regulations for Judicial Insolvency Proceedings50
 
2.3%
Pillar III: Operational Efficiency of Establishing a Business Location50
 
2.3%
Utility Services Overall50
 
2.3%
Business Entry Overall50
 
2.3%
International Trade Overall50
 
2.3%
Other values (33)1650
76.7%

Length

2025-12-14T17:07:51.308750image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pillar1650
 
10.6%
of1500
 
9.7%
services800
 
5.2%
quality700
 
4.5%
for600
 
3.9%
regulations550
 
3.5%
iii500
 
3.2%
ii500
 
3.2%
i500
 
3.2%
overall500
 
3.2%
Other values (61)7700
49.7%

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

Score
Real number (ℝ≥0)

Distinct2037
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.73478152
Minimum0
Maximum100
Zeros12
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size16.9 KiB
2025-12-14T17:07:51.479556image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.4083315
Q147.76666475
median61.47152773
Q373.39722158
95-th percentile88.99999954
Maximum100
Range100
Interquartile range (IQR)25.63055683

Descriptive statistics

Standard deviation19.40334042
Coefficient of variation (CV)0.3248248328
Kurtosis0.1225122101
Mean59.73478152
Median Absolute Deviation (MAD)12.86153603
Skewness-0.4845720753
Sum128429.7803
Variance376.4896194
MonotonicityNot monotonic
2025-12-14T17:07:51.659266image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
012
 
0.6%
755
 
0.2%
51.255
 
0.2%
994
 
0.2%
52.254
 
0.2%
83.333333333
 
0.1%
99.253
 
0.1%
64.753
 
0.1%
66.53
 
0.1%
18.333333
 
0.1%
Other values (2027)2105
97.9%
ValueCountFrequency (%)
012
0.6%
2.2751322391
 
< 0.1%
2.7777776721
 
< 0.1%
3.2000000481
 
< 0.1%
3.3333332
 
0.1%
3.7037036421
 
< 0.1%
51
 
< 0.1%
5.8333331351
 
< 0.1%
6.4125000241
 
< 0.1%
6.6666671
 
< 0.1%
ValueCountFrequency (%)
1002
0.1%
99.444444421
 
< 0.1%
99.253
0.1%
994
0.2%
98.958335881
 
< 0.1%
98.666664121
 
< 0.1%
98.52
0.1%
98.233334541
 
< 0.1%
983
0.1%
97.949999331
 
< 0.1%

Sample

First rows

EconomyNameEconomyCodeYearMainPillar & TopicScore
0SingaporeSGP2024OverallPillar 1 Regulatory Framework72.371520
1SingaporeSGP2024OverallPillar 2 Public Services70.401100
2SingaporeSGP2024OverallPillar 3 Operational Efficiency87.328702
3EstoniaEST2024OverallPillar 1 Regulatory Framework72.839677
4EstoniaEST2024OverallPillar 2 Public Services73.307109
5EstoniaEST2024OverallPillar 3 Operational Efficiency80.278519
6GeorgiaGEO2024OverallPillar 1 Regulatory Framework77.668010
7GeorgiaGEO2024OverallPillar 2 Public Services63.330620
8GeorgiaGEO2024OverallPillar 3 Operational Efficiency84.746945
9RwandaRWA2024OverallPillar 1 Regulatory Framework70.348831

Last rows

EconomyNameEconomyCodeYearMainPillar & TopicScore
2140West Bank and GazaWBG2024Business InsolvencyPillar II: Quality of Institutional and Operational Infrastructure for Judicial Insolvency Proceedings5.00000
2141West Bank and GazaWBG2024Business InsolvencyPillar III: Operational Efficiency of Resolving Judicial Insolvency Proceedings0.00000
2142IraqIRQ2024Business InsolvencyBusiness Insolvency Overall6.74074
2143IraqIRQ2024Business InsolvencyPillar I: Quality of Regulations for Judicial Insolvency Proceedings20.22222
2144IraqIRQ2024Business InsolvencyPillar II: Quality of Institutional and Operational Infrastructure for Judicial Insolvency Proceedings0.00000
2145IraqIRQ2024Business InsolvencyPillar III: Operational Efficiency of Resolving Judicial Insolvency Proceedings0.00000
2146Timor-LesteTMP2024Business InsolvencyBusiness Insolvency Overall0.00000
2147Timor-LesteTMP2024Business InsolvencyPillar I: Quality of Regulations for Judicial Insolvency Proceedings0.00000
2148Timor-LesteTMP2024Business InsolvencyPillar II: Quality of Institutional and Operational Infrastructure for Judicial Insolvency Proceedings0.00000
2149Timor-LesteTMP2024Business InsolvencyPillar III: Operational Efficiency of Resolving Judicial Insolvency Proceedings0.00000