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

Text4
Numeric2

Alerts

Year has constant value ""Constant

Reproduction

Analysis started2026-08-19 00:33:45.131554
Analysis finished2026-08-19 00:33:45.527830
Duration0.4 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

EconomyName
Text

Distinct55
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
2026-08-19T07:33:46.206086image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length24
Median length19
Mean length9.354883721
Min length4

Characters and Unicode

Total characters20113
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
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
ValueCountFrequency (%)
republic 129
 
4.3%
and 86
 
2.9%
singapore 43
 
1.4%
new 43
 
1.4%
north 43
 
1.4%
colombia 43
 
1.4%
croatia 43
 
1.4%
togo 43
 
1.4%
zealand 43
 
1.4%
slovak 43
 
1.4%
Other values (60) 2415
81.2%
2026-08-19T07:33:47.724687image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2924
 
14.5%
e 1532
 
7.6%
o 1505
 
7.5%
i 1333
 
6.6%
n 1310
 
6.5%
r 1075
 
5.3%
824
 
4.1%
l 688
 
3.4%
t 688
 
3.4%
s 645
 
3.2%
Other values (39) 7589
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16156
80.3%
Uppercase Letter 3017
 
15.0%
Space Separator 824
 
4.1%
Other Punctuation 54
 
0.3%
Dash Punctuation 43
 
0.2%
Final Punctuation 19
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2924
18.1%
e 1532
 
9.5%
o 1505
 
9.3%
i 1333
 
8.3%
n 1310
 
8.1%
r 1075
 
6.7%
l 688
 
4.3%
t 688
 
4.3%
s 645
 
4.0%
g 602
 
3.7%
Other values (16) 3854
23.9%
Uppercase Letter
ValueCountFrequency (%)
C 344
11.4%
R 301
10.0%
S 301
10.0%
M 258
 
8.6%
B 258
 
8.6%
P 215
 
7.1%
G 215
 
7.1%
T 156
 
5.2%
N 152
 
5.0%
I 129
 
4.3%
Other values (8) 688
22.8%
Other Punctuation
ValueCountFrequency (%)
, 50
92.6%
' 4
 
7.4%
Space Separator
ValueCountFrequency (%)
824
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19173
95.3%
Common 940
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2924
15.3%
e 1532
 
8.0%
o 1505
 
7.8%
i 1333
 
7.0%
n 1310
 
6.8%
r 1075
 
5.6%
l 688
 
3.6%
t 688
 
3.6%
s 645
 
3.4%
g 602
 
3.1%
Other values (34) 6871
35.8%
Common
ValueCountFrequency (%)
824
87.7%
, 50
 
5.3%
- 43
 
4.6%
’ 19
 
2.0%
' 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20051
99.7%
None 43
 
0.2%
Punctuation 19
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2924
 
14.6%
e 1532
 
7.6%
o 1505
 
7.5%
i 1333
 
6.6%
n 1310
 
6.5%
r 1075
 
5.4%
824
 
4.1%
l 688
 
3.4%
t 688
 
3.4%
s 645
 
3.2%
Other values (37) 7527
37.5%
None
ValueCountFrequency (%)
ô 43
100.0%
Punctuation
ValueCountFrequency (%)
’ 19
100.0%

EconomyCode
Text

Distinct50
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
2026-08-19T07:33:48.637125image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6450
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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
ValueCountFrequency (%)
sgp 43
 
2.0%
col 43
 
2.0%
tgo 43
 
2.0%
geo 43
 
2.0%
rwa 43
 
2.0%
hun 43
 
2.0%
prt 43
 
2.0%
svk 43
 
2.0%
bgr 43
 
2.0%
hkg 43
 
2.0%
Other values (40) 1720
80.0%
2026-08-19T07:33:49.848315image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 516
 
8.0%
R 516
 
8.0%
G 516
 
8.0%
S 387
 
6.0%
P 344
 
5.3%
B 344
 
5.3%
L 301
 
4.7%
H 301
 
4.7%
T 301
 
4.7%
A 301
 
4.7%
Other values (15) 2623
40.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6450
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 516
 
8.0%
R 516
 
8.0%
G 516
 
8.0%
S 387
 
6.0%
P 344
 
5.3%
B 344
 
5.3%
L 301
 
4.7%
H 301
 
4.7%
T 301
 
4.7%
A 301
 
4.7%
Other values (15) 2623
40.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 6450
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 516
 
8.0%
R 516
 
8.0%
G 516
 
8.0%
S 387
 
6.0%
P 344
 
5.3%
B 344
 
5.3%
L 301
 
4.7%
H 301
 
4.7%
T 301
 
4.7%
A 301
 
4.7%
Other values (15) 2623
40.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 516
 
8.0%
R 516
 
8.0%
G 516
 
8.0%
S 387
 
6.0%
P 344
 
5.3%
B 344
 
5.3%
L 301
 
4.7%
H 301
 
4.7%
T 301
 
4.7%
A 301
 
4.7%
Other values (15) 2623
40.7%

Year
Real number (ℝ)

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2024
Minimum2024
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.9 KiB
2026-08-19T07:33:50.240472image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2024
5-th percentile2024
Q12024
median2024
Q32024
95-th percentile2024
Maximum2024
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean2024
Median Absolute Deviation (MAD)0
Skewness0
Sum4351600
Variance0
MonotonicityIncreasing
2026-08-19T07:33:50.524163image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
2024 2150
100.0%
ValueCountFrequency (%)
2024 2150
100.0%
ValueCountFrequency (%)
2024 2150
100.0%

Main
Text

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
2026-08-19T07:33:51.008209image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length19
Median length17
Mean length14.62790698
Min length5

Characters and Unicode

Total characters31450
Distinct characters33
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
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
ValueCountFrequency (%)
business 600
16.0%
services 400
 
10.7%
entry 200
 
5.3%
location 200
 
5.3%
utility 200
 
5.3%
labor 200
 
5.3%
financial 200
 
5.3%
international 200
 
5.3%
trade 200
 
5.3%
taxation 200
 
5.3%
Other values (6) 1150
30.7%
2026-08-19T07:33:51.975234image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 3200
 
10.2%
n 3000
 
9.5%
e 2950
 
9.4%
s 2800
 
8.9%
t 2400
 
7.6%
a 2150
 
6.8%
o 2000
 
6.4%
1600
 
5.1%
r 1550
 
4.9%
l 1300
 
4.1%
Other values (23) 8500
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26100
83.0%
Uppercase Letter 3750
 
11.9%
Space Separator 1600
 
5.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3200
12.3%
n 3000
11.5%
e 2950
11.3%
s 2800
10.7%
t 2400
9.2%
a 2150
8.2%
o 2000
7.7%
r 1550
5.9%
l 1300
 
5.0%
c 1000
 
3.8%
Other values (9) 3750
14.4%
Uppercase Letter
ValueCountFrequency (%)
B 600
16.0%
L 400
10.7%
S 400
10.7%
I 400
10.7%
T 400
10.7%
C 200
 
5.3%
M 200
 
5.3%
R 200
 
5.3%
D 200
 
5.3%
U 200
 
5.3%
Other values (3) 550
14.7%
Space Separator
ValueCountFrequency (%)
1600
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29850
94.9%
Common 1600
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3200
10.7%
n 3000
 
10.1%
e 2950
 
9.9%
s 2800
 
9.4%
t 2400
 
8.0%
a 2150
 
7.2%
o 2000
 
6.7%
r 1550
 
5.2%
l 1300
 
4.4%
c 1000
 
3.4%
Other values (22) 7500
25.1%
Common
ValueCountFrequency (%)
1600
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 3200
 
10.2%
n 3000
 
9.5%
e 2950
 
9.4%
s 2800
 
8.9%
t 2400
 
7.6%
a 2150
 
6.8%
o 2000
 
6.4%
1600
 
5.1%
r 1550
 
4.9%
l 1300
 
4.1%
Other values (23) 8500
27.0%

Pillar & Topic
Text

Distinct43
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size16.9 KiB
2026-08-19T07:33:52.844210image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length102
Median length63
Mean length52.30232558
Min length13

Characters and Unicode

Total characters112450
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
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
ValueCountFrequency (%)
pillar 1650
 
10.6%
of 1500
 
9.7%
services 800
 
5.2%
quality 700
 
4.5%
for 600
 
3.9%
regulations 550
 
3.5%
iii 500
 
3.2%
overall 500
 
3.2%
ii 500
 
3.2%
i 500
 
3.2%
Other values (61) 7700
49.7%
2026-08-19T07:33:54.115230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13350
 
11.9%
i 10350
 
9.2%
a 8050
 
7.2%
l 8000
 
7.1%
e 7150
 
6.4%
r 6700
 
6.0%
o 6650
 
5.9%
n 6300
 
5.6%
t 5650
 
5.0%
s 4350
 
3.9%
Other values (39) 35900
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 83550
74.3%
Uppercase Letter 13800
 
12.3%
Space Separator 13350
 
11.9%
Other Punctuation 1600
 
1.4%
Decimal Number 150
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 10350
12.4%
a 8050
9.6%
l 8000
9.6%
e 7150
8.6%
r 6700
8.0%
o 6650
8.0%
n 6300
 
7.5%
t 5650
 
6.8%
s 4350
 
5.2%
c 3850
 
4.6%
Other values (14) 16500
19.7%
Uppercase Letter
ValueCountFrequency (%)
I 3750
27.2%
P 2600
18.8%
O 950
 
6.9%
R 900
 
6.5%
S 900
 
6.5%
E 850
 
6.2%
Q 700
 
5.1%
T 550
 
4.0%
B 450
 
3.3%
L 400
 
2.9%
Other values (9) 1750
12.7%
Decimal Number
ValueCountFrequency (%)
2 50
33.3%
1 50
33.3%
3 50
33.3%
Other Punctuation
ValueCountFrequency (%)
: 1500
93.8%
, 100
 
6.2%
Space Separator
ValueCountFrequency (%)
13350
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 97350
86.6%
Common 15100
 
13.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 10350
 
10.6%
a 8050
 
8.3%
l 8000
 
8.2%
e 7150
 
7.3%
r 6700
 
6.9%
o 6650
 
6.8%
n 6300
 
6.5%
t 5650
 
5.8%
s 4350
 
4.5%
c 3850
 
4.0%
Other values (33) 30300
31.1%
Common
ValueCountFrequency (%)
13350
88.4%
: 1500
 
9.9%
, 100
 
0.7%
2 50
 
0.3%
1 50
 
0.3%
3 50
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13350
 
11.9%
i 10350
 
9.2%
a 8050
 
7.2%
l 8000
 
7.1%
e 7150
 
6.4%
r 6700
 
6.0%
o 6650
 
5.9%
n 6300
 
5.6%
t 5650
 
5.0%
s 4350
 
3.9%
Other values (39) 35900
31.9%

Score
Real number (ℝ)

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
2026-08-19T07:33:54.593401image/svg+xmlMatplotlib v3.8.4, 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
2026-08-19T07:33:55.022078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
0.6%
51.25 5
 
0.2%
75 5
 
0.2%
52.25 4
 
0.2%
99 4
 
0.2%
64.75 3
 
0.1%
66.5 3
 
0.1%
99.25 3
 
0.1%
91.66666667 3
 
0.1%
13.33333 3
 
0.1%
Other values (2027) 2105
97.9%
ValueCountFrequency (%)
0 12
0.6%
2.275132239 1
 
< 0.1%
2.777777672 1
 
< 0.1%
3.200000048 1
 
< 0.1%
3.333333 2
 
0.1%
ValueCountFrequency (%)
100 2
0.1%
99.44444442 1
 
< 0.1%
99.25 3
0.1%
99 4
0.2%
98.95833588 1
 
< 0.1%