Overview

Dataset statistics

Number of variables4
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory36.3 B

Variable types

Numeric3
Text1

Alerts

property_cd has unique valuesUnique
property_nm has unique valuesUnique
property_la has unique valuesUnique
property_lo has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:51:21.119637
Analysis finished2023-12-10 09:51:23.217817
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

property_cd
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30026267
Minimum23184
Maximum1.0001173 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:51:23.410402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23184
5-th percentile23206.95
Q123278.5
median23493
Q323619.75
95-th percentile23713.2
Maximum1.0001173 × 109
Range1.0000941 × 109
Interquartile range (IQR)341.25

Descriptive statistics

Standard deviation1.7146269 × 108
Coefficient of variation (CV)5.7104233
Kurtosis29.897775
Mean30026267
Median Absolute Deviation (MAD)172
Skewness5.5946495
Sum3.0026267 × 109
Variance2.9399456 × 1016
MonotonicityNot monotonic
2023-12-10T18:51:23.791183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23184 1
 
1.0%
23559 1
 
1.0%
23606 1
 
1.0%
23602 1
 
1.0%
23600 1
 
1.0%
23594 1
 
1.0%
23589 1
 
1.0%
23587 1
 
1.0%
23585 1
 
1.0%
23583 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
23184 1
1.0%
23196 1
1.0%
23197 1
1.0%
23204 1
1.0%
23206 1
1.0%
23207 1
1.0%
23216 1
1.0%
23223 1
1.0%
23224 1
1.0%
23227 1
1.0%
ValueCountFrequency (%)
1000117284 1
1.0%
1000117281 1
1.0%
1000117277 1
1.0%
23720 1
1.0%
23717 1
1.0%
23713 1
1.0%
23708 1
1.0%
23707 1
1.0%
23704 1
1.0%
23701 1
1.0%

property_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:51:24.456311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length9.01
Min length4

Characters and Unicode

Total characters901
Distinct characters242
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row영등포 라이프스타일 F HOTEL
2nd row양평 돌체파르니엔펜션
3rd row대전 신탄진 거기
4th row강남 렉시
5th row대전 유성 시나브로
ValueCountFrequency (%)
호텔 18
 
6.6%
hotel 7
 
2.6%
대전 6
 
2.2%
안산 5
 
1.8%
신촌 4
 
1.5%
신천 4
 
1.5%
포항 4
 
1.5%
무인텔 3
 
1.1%
대잠동 3
 
1.1%
더 3
 
1.1%
Other values (192) 214
79.0%
2023-12-10T18:51:25.531503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
171
 
19.0%
텔 28
 
3.1%
호 24
 
2.7%
천 22
 
2.4%
동 16
 
1.8%
스 16
 
1.8%
안 14
 
1.6%
대 14
 
1.6%
) 14
 
1.6%
( 14
 
1.6%
Other values (232) 568
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 613
68.0%
Space Separator 171
 
19.0%
Uppercase Letter 71
 
7.9%
Close Punctuation 14
 
1.6%
Open Punctuation 14
 
1.6%
Decimal Number 10
 
1.1%
Lowercase Letter 4
 
0.4%
Other Punctuation 2
 
0.2%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 28
 
4.6%
호 24
 
3.9%
천 22
 
3.6%
동 16
 
2.6%
스 16
 
2.6%
안 14
 
2.3%
대 14
 
2.3%
주 12
 
2.0%
인 12
 
2.0%
신 12
 
2.0%
Other values (195) 443
72.3%
Uppercase Letter
ValueCountFrequency (%)
H 9
12.7%
T 8
11.3%
O 8
11.3%
M 7
9.9%
E 7
9.9%
L 7
9.9%
S 5
7.0%
A 5
7.0%
I 2
 
2.8%
U 2
 
2.8%
Other values (9) 11
15.5%
Decimal Number
ValueCountFrequency (%)
2 3
30.0%
7 2
20.0%
4 1
 
10.0%
5 1
 
10.0%
6 1
 
10.0%
3 1
 
10.0%
9 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
25.0%
e 1
25.0%
t 1
25.0%
o 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 613
68.0%
Common 213
 
23.6%
Latin 75
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 28
 
4.6%
호 24
 
3.9%
천 22
 
3.6%
동 16
 
2.6%
스 16
 
2.6%
안 14
 
2.3%
대 14
 
2.3%
주 12
 
2.0%
인 12
 
2.0%
신 12
 
2.0%
Other values (195) 443
72.3%
Latin
ValueCountFrequency (%)
H 9
12.0%
T 8
10.7%
O 8
10.7%
M 7
9.3%
E 7
9.3%
L 7
9.3%
S 5
 
6.7%
A 5
 
6.7%
I 2
 
2.7%
U 2
 
2.7%
Other values (13) 15
20.0%
Common
ValueCountFrequency (%)
171
80.3%
) 14
 
6.6%
( 14
 
6.6%
2 3
 
1.4%
7 2
 
0.9%
4 1
 
0.5%
- 1
 
0.5%
5 1
 
0.5%
6 1
 
0.5%
. 1
 
0.5%
Other values (4) 4
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 613
68.0%
ASCII 288
32.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
171
59.4%
) 14
 
4.9%
( 14
 
4.9%
H 9
 
3.1%
T 8
 
2.8%
O 8
 
2.8%
M 7
 
2.4%
E 7
 
2.4%
L 7
 
2.4%
S 5
 
1.7%
Other values (27) 38
 
13.2%
Hangul
ValueCountFrequency (%)
텔 28
 
4.6%
호 24
 
3.9%
천 22
 
3.6%
동 16
 
2.6%
스 16
 
2.6%
안 14
 
2.3%
대 14
 
2.3%
주 12
 
2.0%
인 12
 
2.0%
신 12
 
2.0%
Other values (195) 443
72.3%

property_la
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.926531
Minimum34.773795
Maximum38.141341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:51:25.832780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.773795
5-th percentile35.178846
Q136.319285
median37.426148
Q337.512442
95-th percentile37.637908
Maximum38.141341
Range3.3675463
Interquartile range (IQR)1.1931568

Descriptive statistics

Standard deviation0.84416966
Coefficient of variation (CV)0.02286079
Kurtosis-0.21857828
Mean36.926531
Median Absolute Deviation (MAD)0.15229
Skewness-1.0200576
Sum3692.6531
Variance0.71262241
MonotonicityNot monotonic
2023-12-10T18:51:26.115867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5171818 1
 
1.0%
36.8071687 1
 
1.0%
37.3450484 1
 
1.0%
37.2689892 1
 
1.0%
37.8823501 1
 
1.0%
36.1372858 1
 
1.0%
37.501168 1
 
1.0%
37.6327502 1
 
1.0%
37.5463023 1
 
1.0%
36.3615464 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
34.773795 1
1.0%
34.9072150902 1
1.0%
35.0286317 1
1.0%
35.1347562 1
1.0%
35.162714 1
1.0%
35.1796948 1
1.0%
35.1913689 1
1.0%
35.1939818 1
1.0%
35.2361496 1
1.0%
35.5377419 1
1.0%
ValueCountFrequency (%)
38.1413413 1
1.0%
37.8823501 1
1.0%
37.8694442 1
1.0%
37.7361932 1
1.0%
37.7359064 1
1.0%
37.6327502 1
1.0%
37.623809935348845 1
1.0%
37.6137107586 1
1.0%
37.5979173 1
1.0%
37.5961587 1
1.0%

property_lo
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.41135
Minimum126.32086
Maximum129.3769
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:51:26.415233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.32086
5-th percentile126.68436
Q1126.90603
median127.08091
Q3127.55317
95-th percentile129.2649
Maximum129.3769
Range3.0560328
Interquartile range (IQR)0.64714218

Descriptive statistics

Standard deviation0.8095829
Coefficient of variation (CV)0.0063540878
Kurtosis0.41598684
Mean127.41135
Median Absolute Deviation (MAD)0.2475562
Skewness1.2823039
Sum12741.135
Variance0.65542446
MonotonicityNot monotonic
2023-12-10T18:51:26.723092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9112166 1
 
1.0%
127.1488898 1
 
1.0%
127.9292108 1
 
1.0%
127.00150570000004 1
 
1.0%
127.72754600000007 1
 
1.0%
128.418977 1
 
1.0%
127.0404898 1
 
1.0%
127.0229203 1
 
1.0%
126.84835880000004 1
 
1.0%
127.3779247 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.3208648 1
1.0%
126.3344323 1
1.0%
126.4607968821 1
1.0%
126.67882113355807 1
1.0%
126.6837308 1
1.0%
126.6843976 1
1.0%
126.70162359999996 1
1.0%
126.7024088 1
1.0%
126.7270534 1
1.0%
126.741041 1
1.0%
ValueCountFrequency (%)
129.3768976 1
1.0%
129.34788560000004 1
1.0%
129.345999 1
1.0%
129.3455431 1
1.0%
129.33347819999994 1
1.0%
129.2612857 1
1.0%
129.2037731 1
1.0%
129.11635909999995 1
1.0%
129.09372050000002 1
1.0%
128.90198929999997 1
1.0%

Interactions

2023-12-10T18:51:22.384004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:21.450618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:21.908603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:22.541551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:21.600481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:22.068398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:22.733852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:21.745882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:51:22.229304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:51:26.935180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
property_cdproperty_nmproperty_laproperty_lo
property_cd1.0001.0000.2170.415
property_nm1.0001.0001.0001.000
property_la0.2171.0001.0000.896
property_lo0.4151.0000.8961.000
2023-12-10T18:51:27.110515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
property_cdproperty_laproperty_lo
property_cd1.000-0.133-0.015
property_la-0.1331.000-0.420
property_lo-0.015-0.4201.000

Missing values

2023-12-10T18:51:22.978952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:51:23.150279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

property_cdproperty_nmproperty_laproperty_lo
023184영등포 라이프스타일 F HOTEL37.517182126.911217
11000117277양평 돌체파르니엔펜션37.531411127.482184
223196대전 신탄진 거기36.450799127.431669
323197강남 렉시37.498792127.033956
423204대전 유성 시나브로36.356873127.349172
523206부천(상동) MY HOTEL37.506612126.756644
623207역삼 벤37.500706127.039849
71000117281강화도 야생화카페펜션37.613711126.460797
823216서울대입구 폭스37.483092126.954564
923223양재 호텔 신트라37.48467127.029226
property_cdproperty_nmproperty_laproperty_lo
9023683안산 IMT37.309666126.868769
9123686광주 곤지암 윌 무인텔37.361815127.313955
9223693광주 신안동 여기서자자35.162714126.906257
9323701부천 노블레스37.484984126.785746
9423704인천(주안) 더자자37.460702126.684398
9523707경산 러브웨이35.823273128.741333
9623708포항 영일대 포스36.053583129.376898
9723713화순 퀸 무인텔35.028632126.905344
9823717동탄 첼시37.20504127.073226
9923720김해 어방동 6935.23615128.901989