Overview

Dataset statistics

Number of variables27
Number of observations100
Missing cells340
Missing cells (%)12.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.3 KiB
Average record size in memory228.3 B

Variable types

Text10
Categorical9
Numeric7
Unsupported1

Alerts

lclas has constant value ""Constant
mlsfc has constant value ""Constant
branch_nm has constant value ""Constant
lst_updt_dt has constant value ""Constant
data_orgn has constant value ""Constant
file_name has constant value ""Constant
base_ymd has constant value ""Constant
branch_nm has 99 (99.0%) missing valuesMissing
sub_nm has 100 (100.0%) missing valuesMissing
ri_nm has 78 (78.0%) missing valuesMissing
rd_cd has 21 (21.0%) missing valuesMissing
rd_nm has 21 (21.0%) missing valuesMissing
bld_num has 21 (21.0%) missing valuesMissing
id has unique valuesUnique
id_poi has unique valuesUnique
pnu has unique valuesUnique
x has unique valuesUnique
y has unique valuesUnique
grid_cd has unique valuesUnique
sub_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 09:57:46.201373
Analysis finished2023-12-10 09:57:47.229095
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:47.545172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1900
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowKCDRTPO21N000000001
2nd rowKCDRTPO21N000033675
3rd rowKCDRTPO21N000000003
4th rowKCDRTPO21N000000004
5th rowKCDRTPO21N000000005
ValueCountFrequency (%)
kcdrtpo21n000000001 1
 
1.0%
kcdrtpo21n000000063 1
 
1.0%
kcdrtpo21n000000074 1
 
1.0%
kcdrtpo21n000000073 1
 
1.0%
kcdrtpo21n000000072 1
 
1.0%
kcdrtpo21n000000071 1
 
1.0%
kcdrtpo21n000000070 1
 
1.0%
kcdrtpo21n000000069 1
 
1.0%
kcdrtpo21n000000068 1
 
1.0%
kcdrtpo21n000000067 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:57:48.235334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 708
37.3%
1 121
 
6.4%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
T 100
 
5.3%
R 100
 
5.3%
Other values (8) 253
 
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
57.9%
Uppercase Letter 800
42.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 708
64.4%
1 121
 
11.0%
2 118
 
10.7%
3 25
 
2.3%
6 24
 
2.2%
7 24
 
2.2%
5 21
 
1.9%
4 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
K 100
12.5%
O 100
12.5%
C 100
12.5%
N 100
12.5%
P 100
12.5%
T 100
12.5%
R 100
12.5%
D 100
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
57.9%
Latin 800
42.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 708
64.4%
1 121
 
11.0%
2 118
 
10.7%
3 25
 
2.3%
6 24
 
2.2%
7 24
 
2.2%
5 21
 
1.9%
4 20
 
1.8%
9 20
 
1.8%
8 19
 
1.7%
Latin
ValueCountFrequency (%)
K 100
12.5%
O 100
12.5%
C 100
12.5%
N 100
12.5%
P 100
12.5%
T 100
12.5%
R 100
12.5%
D 100
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 708
37.3%
1 121
 
6.4%
2 118
 
6.2%
K 100
 
5.3%
O 100
 
5.3%
C 100
 
5.3%
N 100
 
5.3%
P 100
 
5.3%
T 100
 
5.3%
R 100
 
5.3%
Other values (8) 253
 
13.3%

lclas
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
장소
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row장소
2nd row장소
3rd row장소
4th row장소
5th row장소

Common Values

ValueCountFrequency (%)
장소 100
100.0%

Length

2023-12-10T18:57:48.478556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:48.655120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장소 100
100.0%

mlsfc
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
교통
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교통
2nd row교통
3rd row교통
4th row교통
5th row교통

Common Values

ValueCountFrequency (%)
교통 100
100.0%

Length

2023-12-10T18:57:48.890606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:49.142249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통 100
100.0%

id_poi
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11409578
Minimum8276362
Maximum22216214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:49.394357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8276362
5-th percentile10268596
Q110270366
median10274288
Q311363486
95-th percentile14256499
Maximum22216214
Range13939852
Interquartile range (IQR)1093120.2

Descriptive statistics

Standard deviation2346167.9
Coefficient of variation (CV)0.20563143
Kurtosis11.664096
Mean11409578
Median Absolute Deviation (MAD)5572.5
Skewness3.1447402
Sum1.1409578 × 109
Variance5.504504 × 1012
MonotonicityNot monotonic
2023-12-10T18:57:49.742005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8276362 1
 
1.0%
10616660 1
 
1.0%
11321433 1
 
1.0%
11299114 1
 
1.0%
11298306 1
 
1.0%
11294988 1
 
1.0%
11262924 1
 
1.0%
11254588 1
 
1.0%
11176471 1
 
1.0%
11100146 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
8276362 1
1.0%
10268374 1
1.0%
10268409 1
1.0%
10268452 1
1.0%
10268453 1
1.0%
10268604 1
1.0%
10268696 1
1.0%
10268734 1
1.0%
10268740 1
1.0%
10268772 1
1.0%
ValueCountFrequency (%)
22216214 1
1.0%
22203593 1
1.0%
22188673 1
1.0%
14261462 1
1.0%
14258103 1
1.0%
14256415 1
1.0%
14253577 1
1.0%
14252552 1
1.0%
14220806 1
1.0%
14109449 1
1.0%

poi_nm
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:50.213465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length9.22
Min length3

Characters and Unicode

Total characters922
Distinct characters200
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row숭의여자대학교주차장
2nd row영남알프스국제클라이밍장3주차장
3rd row신선3동공영주차장
4th row공영주차장
5th row신정1동노외공영주차장
ValueCountFrequency (%)
공영주차장 2
 
2.0%
중산리주차장 1
 
1.0%
강원대학교병원강원대병원2주차장 1
 
1.0%
쏠비치양양주차장c 1
 
1.0%
퍼니스카페앤라운지주차장 1
 
1.0%
마우나오션cc주차장 1
 
1.0%
천안축구센터주차장1 1
 
1.0%
금산종합운동장후문주차장 1
 
1.0%
증평군청주차장 1
 
1.0%
신구대식물원주차장 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T18:57:50.915902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 111
 
12.0%
주 105
 
11.4%
차 102
 
11.1%
원 30
 
3.3%
공 27
 
2.9%
동 19
 
2.1%
영 16
 
1.7%
대 13
 
1.4%
수 12
 
1.3%
산 12
 
1.3%
Other values (190) 475
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 888
96.3%
Decimal Number 23
 
2.5%
Uppercase Letter 11
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 111
 
12.5%
주 105
 
11.8%
차 102
 
11.5%
원 30
 
3.4%
공 27
 
3.0%
동 19
 
2.1%
영 16
 
1.8%
대 13
 
1.5%
수 12
 
1.4%
산 12
 
1.4%
Other values (179) 441
49.7%
Decimal Number
ValueCountFrequency (%)
2 8
34.8%
1 7
30.4%
3 4
17.4%
9 2
 
8.7%
6 1
 
4.3%
5 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 5
45.5%
K 2
 
18.2%
S 2
 
18.2%
P 1
 
9.1%
B 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 888
96.3%
Common 23
 
2.5%
Latin 11
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 111
 
12.5%
주 105
 
11.8%
차 102
 
11.5%
원 30
 
3.4%
공 27
 
3.0%
동 19
 
2.1%
영 16
 
1.8%
대 13
 
1.5%
수 12
 
1.4%
산 12
 
1.4%
Other values (179) 441
49.7%
Common
ValueCountFrequency (%)
2 8
34.8%
1 7
30.4%
3 4
17.4%
9 2
 
8.7%
6 1
 
4.3%
5 1
 
4.3%
Latin
ValueCountFrequency (%)
C 5
45.5%
K 2
 
18.2%
S 2
 
18.2%
P 1
 
9.1%
B 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 888
96.3%
ASCII 34
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 111
 
12.5%
주 105
 
11.8%
차 102
 
11.5%
원 30
 
3.4%
공 27
 
3.0%
동 19
 
2.1%
영 16
 
1.8%
대 13
 
1.5%
수 12
 
1.4%
산 12
 
1.4%
Other values (179) 441
49.7%
ASCII
ValueCountFrequency (%)
2 8
23.5%
1 7
20.6%
C 5
14.7%
3 4
11.8%
K 2
 
5.9%
S 2
 
5.9%
9 2
 
5.9%
6 1
 
2.9%
5 1
 
2.9%
P 1
 
2.9%

branch_nm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing99
Missing (%)99.0%
Memory size932.0 B
2023-12-10T18:57:51.150812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
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

Unique1 ?
Unique (%)100.0%

Sample

1st row예술공원노외
ValueCountFrequency (%)
예술공원노외 1
100.0%
2023-12-10T18:57:51.569337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
예 1
16.7%
술 1
16.7%
공 1
16.7%
원 1
16.7%
노 1
16.7%
외 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
예 1
16.7%
술 1
16.7%
공 1
16.7%
원 1
16.7%
노 1
16.7%
외 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
예 1
16.7%
술 1
16.7%
공 1
16.7%
원 1
16.7%
노 1
16.7%
외 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
예 1
16.7%
술 1
16.7%
공 1
16.7%
원 1
16.7%
노 1
16.7%
외 1
16.7%

sub_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

mcate_cd
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
160302
57 
160304
29 
160301
12 
160303
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row160302
2nd row160302
3rd row160301
4th row160301
5th row160301

Common Values

ValueCountFrequency (%)
160302 57
57.0%
160304 29
29.0%
160301 12
 
12.0%
160303 2
 
2.0%

Length

2023-12-10T18:57:51.774082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:51.931190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
160302 57
57.0%
160304 29
29.0%
160301 12
 
12.0%
160303 2
 
2.0%

mcate_nm
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
부속주차장
57 
일반주차장
29 
공영주차장
12 
주차빌딩
 
2

Length

Max length5
Median length5
Mean length4.98
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부속주차장
2nd row부속주차장
3rd row공영주차장
4th row공영주차장
5th row공영주차장

Common Values

ValueCountFrequency (%)
부속주차장 57
57.0%
일반주차장 29
29.0%
공영주차장 12
 
12.0%
주차빌딩 2
 
2.0%

Length

2023-12-10T18:57:52.119280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:52.308015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부속주차장 57
57.0%
일반주차장 29
29.0%
공영주차장 12
 
12.0%
주차빌딩 2
 
2.0%

pnu
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4574245 × 1018
Minimum1.1110173 × 1018
Maximum5.0110109 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:52.561454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110173 × 1018
5-th percentile1.1300602 × 1018
Q12.7955357 × 1018
median4.1140607 × 1018
Q34.5140105 × 1018
95-th percentile4.8170104 × 1018
Maximum5.0110109 × 1018
Range3.8999936 × 1018
Interquartile range (IQR)1.7184748 × 1018

Descriptive statistics

Standard deviation1.2985935 × 1018
Coefficient of variation (CV)0.37559561
Kurtosis-0.80734264
Mean3.4574245 × 1018
Median Absolute Deviation (MAD)6.9825075 × 1017
Skewness-0.75907783
Sum-4.7456855 × 1018
Variance1.686345 × 1036
MonotonicityNot monotonic
2023-12-10T18:57:52.849732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1114014200100080003 1
 
1.0%
4128510100108140000 1
 
1.0%
4793025023101190000 1
 
1.0%
4283032025100230004 1
 
1.0%
2914012000108810004 1
 
1.0%
4713032027201400001 1
 
1.0%
4117110100108630000 1
 
1.0%
4413310200103540000 1
 
1.0%
4471025023100730000 1
 
1.0%
4374525026101000000 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1111017300100011407 1
1.0%
1114014200100080003 1
1.0%
1117012800100400518 1
1.0%
1117013100107470007 1
1.0%
1121510500106310018 1
1.0%
1130510200105160002 1
1.0%
1130510300100570016 1
1.0%
1141012000100120001 1
1.0%
1144012500105330001 1
1.0%
1144012700104810006 1
1.0%
ValueCountFrequency (%)
5011010900116110002 1
1.0%
4886036021201120001 1
1.0%
4873025024105810001 1
1.0%
4831033022106370005 1
1.0%
4817010900100110008 1
1.0%
4817010400104860001 1
1.0%
4812312700100250000 1
1.0%
4812310200106280006 1
1.0%
4793025023101190000 1
1.0%
4790034037100910000 1
1.0%

sido_nm
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
18 
경기도
15 
전라남도
8 
강원도
8 
광주광역시
8 
Other values (11)
43 

Length

Max length7
Median length5
Mean length4.23
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row서울특별시
2nd row울산광역시
3rd row부산광역시
4th row경기도
5th row울산광역시

Common Values

ValueCountFrequency (%)
서울특별시 18
18.0%
경기도 15
15.0%
전라남도 8
8.0%
강원도 8
8.0%
광주광역시 8
8.0%
경상남도 7
 
7.0%
경상북도 7
 
7.0%
부산광역시 5
 
5.0%
인천광역시 5
 
5.0%
전라북도 4
 
4.0%
Other values (6) 15
15.0%

Length

2023-12-10T18:57:53.159286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 18
18.0%
경기도 15
15.0%
전라남도 8
8.0%
강원도 8
8.0%
광주광역시 8
8.0%
경상남도 7
 
7.0%
경상북도 7
 
7.0%
부산광역시 5
 
5.0%
인천광역시 5
 
5.0%
전라북도 4
 
4.0%
Other values (6) 15
15.0%

sgg_nm
Text

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:53.708883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.53
Min length2

Characters and Unicode

Total characters353
Distinct characters72
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)39.0%

Sample

1st row중구
2nd row울주군
3rd row영도구
4th row안양시 만안구
5th row남구
ValueCountFrequency (%)
북구 6
 
5.2%
수원시 6
 
5.2%
서구 5
 
4.3%
팔달구 4
 
3.4%
마포구 3
 
2.6%
남구 3
 
2.6%
익산시 2
 
1.7%
강북구 2
 
1.7%
창원시 2
 
1.7%
성산구 2
 
1.7%
Other values (62) 81
69.8%
2023-12-10T18:57:54.621466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 61
 
17.3%
시 43
 
12.2%
군 17
 
4.8%
16
 
4.5%
원 12
 
3.4%
산 12
 
3.4%
양 10
 
2.8%
포 9
 
2.5%
수 9
 
2.5%
주 9
 
2.5%
Other values (62) 155
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 337
95.5%
Space Separator 16
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 61
18.1%
시 43
 
12.8%
군 17
 
5.0%
원 12
 
3.6%
산 12
 
3.6%
양 10
 
3.0%
포 9
 
2.7%
수 9
 
2.7%
주 9
 
2.7%
북 9
 
2.7%
Other values (61) 146
43.3%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 337
95.5%
Common 16
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 61
18.1%
시 43
 
12.8%
군 17
 
5.0%
원 12
 
3.6%
산 12
 
3.6%
양 10
 
3.0%
포 9
 
2.7%
수 9
 
2.7%
주 9
 
2.7%
북 9
 
2.7%
Other values (61) 146
43.3%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 337
95.5%
ASCII 16
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 61
18.1%
시 43
 
12.8%
군 17
 
5.0%
원 12
 
3.6%
산 12
 
3.6%
양 10
 
3.0%
포 9
 
2.7%
수 9
 
2.7%
주 9
 
2.7%
북 9
 
2.7%
Other values (61) 146
43.3%
ASCII
ValueCountFrequency (%)
16
100.0%

bemd_nm
Text

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:55.217408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.2
Min length2

Characters and Unicode

Total characters320
Distinct characters109
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)88.0%

Sample

1st row예장동
2nd row상북면
3rd row신선동3가
4th row석수동
5th row신정동
ValueCountFrequency (%)
치평동 2
 
2.0%
상암동 2
 
2.0%
금산읍 2
 
2.0%
송도동 2
 
2.0%
금호동 2
 
2.0%
구례읍 2
 
2.0%
부여읍 1
 
1.0%
영통동 1
 
1.0%
양남면 1
 
1.0%
안양동 1
 
1.0%
Other values (84) 84
84.0%
2023-12-10T18:57:56.790844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 75
23.4%
읍 12
 
3.8%
산 12
 
3.8%
가 11
 
3.4%
면 10
 
3.1%
수 8
 
2.5%
남 8
 
2.5%
금 6
 
1.9%
정 6
 
1.9%
신 5
 
1.6%
Other values (99) 167
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 312
97.5%
Decimal Number 8
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 75
24.0%
읍 12
 
3.8%
산 12
 
3.8%
가 11
 
3.5%
면 10
 
3.2%
수 8
 
2.6%
남 8
 
2.6%
금 6
 
1.9%
정 6
 
1.9%
신 5
 
1.6%
Other values (96) 159
51.0%
Decimal Number
ValueCountFrequency (%)
3 4
50.0%
2 2
25.0%
5 2
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 312
97.5%
Common 8
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 75
24.0%
읍 12
 
3.8%
산 12
 
3.8%
가 11
 
3.5%
면 10
 
3.2%
수 8
 
2.6%
남 8
 
2.6%
금 6
 
1.9%
정 6
 
1.9%
신 5
 
1.6%
Other values (96) 159
51.0%
Common
ValueCountFrequency (%)
3 4
50.0%
2 2
25.0%
5 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 312
97.5%
ASCII 8
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 75
24.0%
읍 12
 
3.8%
산 12
 
3.8%
가 11
 
3.5%
면 10
 
3.2%
수 8
 
2.6%
남 8
 
2.6%
금 6
 
1.9%
정 6
 
1.9%
신 5
 
1.6%
Other values (96) 159
51.0%
ASCII
ValueCountFrequency (%)
3 4
50.0%
2 2
25.0%
5 2
25.0%

ri_nm
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing78
Missing (%)78.0%
Memory size932.0 B
2023-12-10T18:57:57.617808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0909091
Min length2

Characters and Unicode

Total characters68
Distinct characters36
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

Unique20 ?
Unique (%)90.9%

Sample

1st row등억알프스리
2nd row봉동리
3rd row도항리
4th row동성리
5th row동산리
ValueCountFrequency (%)
봉동리 2
 
9.1%
창동리 1
 
4.5%
동남리 1
 
4.5%
형동리 1
 
4.5%
사동리 1
 
4.5%
중산리 1
 
4.5%
연지리 1
 
4.5%
오산리 1
 
4.5%
신대리 1
 
4.5%
하옥리 1
 
4.5%
Other values (11) 11
50.0%
2023-12-10T18:57:58.283815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 22
32.4%
동 8
 
11.8%
산 3
 
4.4%
봉 2
 
2.9%
사 2
 
2.9%
대 1
 
1.5%
병 1
 
1.5%
창 1
 
1.5%
하 1
 
1.5%
옥 1
 
1.5%
Other values (26) 26
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 22
32.4%
동 8
 
11.8%
산 3
 
4.4%
봉 2
 
2.9%
사 2
 
2.9%
대 1
 
1.5%
병 1
 
1.5%
창 1
 
1.5%
하 1
 
1.5%
옥 1
 
1.5%
Other values (26) 26
38.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 22
32.4%
동 8
 
11.8%
산 3
 
4.4%
봉 2
 
2.9%
사 2
 
2.9%
대 1
 
1.5%
병 1
 
1.5%
창 1
 
1.5%
하 1
 
1.5%
옥 1
 
1.5%
Other values (26) 26
38.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 22
32.4%
동 8
 
11.8%
산 3
 
4.4%
봉 2
 
2.9%
사 2
 
2.9%
대 1
 
1.5%
병 1
 
1.5%
창 1
 
1.5%
하 1
 
1.5%
옥 1
 
1.5%
Other values (26) 26
38.2%

beonji
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:58.945202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.5
Min length1

Characters and Unicode

Total characters450
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row8-3
2nd row517
3rd row112-255
4th row240-17
5th row635-6
ValueCountFrequency (%)
119 2
 
2.0%
11-8 1
 
1.0%
881-4 1
 
1.0%
산140-1 1
 
1.0%
863 1
 
1.0%
354 1
 
1.0%
73 1
 
1.0%
100 1
 
1.0%
120-4 1
 
1.0%
552 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T18:58:00.015102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 95
21.1%
- 73
16.2%
2 39
8.7%
3 39
8.7%
5 35
 
7.8%
4 33
 
7.3%
6 33
 
7.3%
8 29
 
6.4%
7 25
 
5.6%
9 23
 
5.1%
Other values (2) 26
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 372
82.7%
Dash Punctuation 73
 
16.2%
Other Letter 5
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 95
25.5%
2 39
10.5%
3 39
10.5%
5 35
 
9.4%
4 33
 
8.9%
6 33
 
8.9%
8 29
 
7.8%
7 25
 
6.7%
9 23
 
6.2%
0 21
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%
Other Letter
ValueCountFrequency (%)
산 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 445
98.9%
Hangul 5
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 95
21.3%
- 73
16.4%
2 39
8.8%
3 39
8.8%
5 35
 
7.9%
4 33
 
7.4%
6 33
 
7.4%
8 29
 
6.5%
7 25
 
5.6%
9 23
 
5.2%
Hangul
ValueCountFrequency (%)
산 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445
98.9%
Hangul 5
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 95
21.3%
- 73
16.4%
2 39
8.8%
3 39
8.8%
5 35
 
7.9%
4 33
 
7.4%
6 33
 
7.4%
8 29
 
6.5%
7 25
 
5.6%
9 23
 
5.2%
Hangul
ValueCountFrequency (%)
산 5
100.0%

badm_cd
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4575534 × 109
Minimum1.1110173 × 109
Maximum5.0110109 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:00.522524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110173 × 109
5-th percentile1.1300602 × 109
Q12.7955357 × 109
median4.1140607 × 109
Q34.5140105 × 109
95-th percentile4.8170104 × 109
Maximum5.0110109 × 109
Range3.8999936 × 109
Interquartile range (IQR)1.7184748 × 109

Descriptive statistics

Standard deviation1.2986631 × 109
Coefficient of variation (CV)0.37560176
Kurtosis-0.80745408
Mean3.4575534 × 109
Median Absolute Deviation (MAD)6.9825075 × 108
Skewness-0.75917152
Sum3.4575534 × 1011
Variance1.686526 × 1018
MonotonicityNot monotonic
2023-12-10T18:58:01.452552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2914012000 2
 
2.0%
4673025021 2
 
2.0%
1144012700 2
 
2.0%
2818510600 2
 
2.0%
1114014200 1
 
1.0%
4111710500 1
 
1.0%
4713032027 1
 
1.0%
4117110100 1
 
1.0%
4413310200 1
 
1.0%
4471025023 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
1111017300 1
1.0%
1114014200 1
1.0%
1117012800 1
1.0%
1117013100 1
1.0%
1121510500 1
1.0%
1130510200 1
1.0%
1130510300 1
1.0%
1141012000 1
1.0%
1144012500 1
1.0%
1144012700 2
2.0%
ValueCountFrequency (%)
5011010900 1
1.0%
4886036021 1
1.0%
4873025024 1
1.0%
4831033022 1
1.0%
4817010900 1
1.0%
4817010400 1
1.0%
4812312700 1
1.0%
4812310200 1
1.0%
4793025023 1
1.0%
4790034037 1
1.0%

hadm_cd
Real number (ℝ)

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4575922 × 109
Minimum1.111065 × 109
Maximum5.011058 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:01.957632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111065 × 109
5-th percentile1.1301114 × 109
Q12.7955795 × 109
median4.1141075 × 109
Q34.514052 × 109
95-th percentile4.8170518 × 109
Maximum5.011058 × 109
Range3.899993 × 109
Interquartile range (IQR)1.7184725 × 109

Descriptive statistics

Standard deviation1.2986526 × 109
Coefficient of variation (CV)0.37559449
Kurtosis-0.80744171
Mean3.4575922 × 109
Median Absolute Deviation (MAD)6.98246 × 108
Skewness-0.75917973
Sum3.4575922 × 1011
Variance1.6864985 × 1018
MonotonicityNot monotonic
2023-12-10T18:58:02.329822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2914074500 2
 
2.0%
4514052000 2
 
2.0%
4471025000 2
 
2.0%
4673025000 2
 
2.0%
1144074000 2
 
2.0%
2917068500 2
 
2.0%
4711352000 2
 
2.0%
2818582000 2
 
2.0%
4128551000 1
 
1.0%
4713032000 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
1111065000 1
1.0%
1114057000 1
1.0%
1117062500 1
1.0%
1117068500 1
1.0%
1121582000 1
1.0%
1130560300 1
1.0%
1130561500 1
1.0%
1141070000 1
1.0%
1144073000 1
1.0%
1144074000 2
2.0%
ValueCountFrequency (%)
5011058000 1
1.0%
4886036000 1
1.0%
4873025000 1
1.0%
4831033000 1
1.0%
4817056500 1
1.0%
4817051500 1
1.0%
4812354000 1
1.0%
4812353000 1
1.0%
4793025000 1
1.0%
4790034000 1
1.0%

rd_cd
Real number (ℝ)

MISSING 

Distinct78
Distinct (%)98.7%
Missing21
Missing (%)21.0%
Infinite0
Infinite (%)0.0%
Mean3.4429846 × 1011
Minimum1.114041 × 1011
Maximum5.0110485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:02.656579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.114041 × 1011
5-th percentile1.1296321 × 1011
Q12.7733807 × 1011
median4.1117318 × 1011
Q34.5135394 × 1011
95-th percentile4.8170243 × 1011
Maximum5.0110485 × 1011
Range3.8970074 × 1011
Interquartile range (IQR)1.7401586 × 1011

Descriptive statistics

Standard deviation1.2936883 × 1011
Coefficient of variation (CV)0.37574619
Kurtosis-0.8137132
Mean3.4429846 × 1011
Median Absolute Deviation (MAD)7.0529155 × 1010
Skewness-0.73119092
Sum2.7199578 × 1013
Variance1.6736295 × 1022
MonotonicityNot monotonic
2023-12-10T18:58:03.028715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
114403113018 2
 
2.0%
411174331137 1
 
1.0%
291403160016 1
 
1.0%
471303305072 1
 
1.0%
441333250045 1
 
1.0%
447103000088 1
 
1.0%
437453014040 1
 
1.0%
261403126004 1
 
1.0%
412853193010 1
 
1.0%
421103218013 1
 
1.0%
Other values (68) 68
68.0%
(Missing) 21
 
21.0%
ValueCountFrequency (%)
111404103215 1
1.0%
111702005005 1
1.0%
111703101018 1
1.0%
112154112416 1
1.0%
113053108003 1
1.0%
113054124043 1
1.0%
114403113018 2
2.0%
114403113025 1
1.0%
114702000003 1
1.0%
115304148097 1
1.0%
ValueCountFrequency (%)
501104847444 1
1.0%
488602345002 1
1.0%
487304820061 1
1.0%
481703332056 1
1.0%
481702332003 1
1.0%
481234784084 1
1.0%
479304775368 1
1.0%
479003307052 1
1.0%
472104727417 1
1.0%
471704721270 1
1.0%

rd_nm
Text

MISSING 

Distinct77
Distinct (%)97.5%
Missing21
Missing (%)21.0%
Memory size932.0 B
2023-12-10T18:58:03.593499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.4810127
Min length3

Characters and Unicode

Total characters354
Distinct characters135
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)96.2%

Sample

1st row소파로2길
2nd row알프스온천5길
3rd row영마루길
4th row예술공원로131번길
5th row월평로
ValueCountFrequency (%)
월드컵로 3
 
3.8%
내방로 1
 
1.3%
소파로2길 1
 
1.3%
영통로214번길 1
 
1.3%
상무누리로 1
 
1.3%
동남로 1
 
1.3%
축구센터로 1
 
1.3%
금산로 1
 
1.3%
광장로 1
 
1.3%
대신공원로 1
 
1.3%
Other values (67) 67
84.8%
2023-12-10T18:58:04.493253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 65
 
18.4%
길 29
 
8.2%
1 12
 
3.4%
번 9
 
2.5%
대 9
 
2.5%
월 6
 
1.7%
5 6
 
1.7%
3 6
 
1.7%
2 6
 
1.7%
원 5
 
1.4%
Other values (125) 201
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
89.5%
Decimal Number 37
 
10.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 65
 
20.5%
길 29
 
9.1%
번 9
 
2.8%
대 9
 
2.8%
월 6
 
1.9%
원 5
 
1.6%
산 5
 
1.6%
동 4
 
1.3%
공 4
 
1.3%
금 4
 
1.3%
Other values (116) 177
55.8%
Decimal Number
ValueCountFrequency (%)
1 12
32.4%
5 6
16.2%
3 6
16.2%
2 6
16.2%
7 2
 
5.4%
4 2
 
5.4%
9 1
 
2.7%
8 1
 
2.7%
0 1
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
89.5%
Common 37
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 65
 
20.5%
길 29
 
9.1%
번 9
 
2.8%
대 9
 
2.8%
월 6
 
1.9%
원 5
 
1.6%
산 5
 
1.6%
동 4
 
1.3%
공 4
 
1.3%
금 4
 
1.3%
Other values (116) 177
55.8%
Common
ValueCountFrequency (%)
1 12
32.4%
5 6
16.2%
3 6
16.2%
2 6
16.2%
7 2
 
5.4%
4 2
 
5.4%
9 1
 
2.7%
8 1
 
2.7%
0 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
89.5%
ASCII 37
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 65
 
20.5%
길 29
 
9.1%
번 9
 
2.8%
대 9
 
2.8%
월 6
 
1.9%
원 5
 
1.6%
산 5
 
1.6%
동 4
 
1.3%
공 4
 
1.3%
금 4
 
1.3%
Other values (116) 177
55.8%
ASCII
ValueCountFrequency (%)
1 12
32.4%
5 6
16.2%
3 6
16.2%
2 6
16.2%
7 2
 
5.4%
4 2
 
5.4%
9 1
 
2.7%
8 1
 
2.7%
0 1
 
2.7%

bld_num
Text

MISSING 

Distinct69
Distinct (%)87.3%
Missing21
Missing (%)21.0%
Memory size932.0 B
2023-12-10T18:58:04.969452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5696203
Min length1

Characters and Unicode

Total characters203
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)77.2%

Sample

1st row10
2nd row103-8
3rd row143
4th row7
5th row25
ValueCountFrequency (%)
7 4
 
5.1%
2 2
 
2.5%
100 2
 
2.5%
14 2
 
2.5%
23 2
 
2.5%
6 2
 
2.5%
20 2
 
2.5%
10 2
 
2.5%
41 1
 
1.3%
88 1
 
1.3%
Other values (59) 59
74.7%
2023-12-10T18:58:05.662823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 34
16.7%
2 31
15.3%
3 23
11.3%
5 20
9.9%
0 17
8.4%
6 16
7.9%
4 15
7.4%
9 13
 
6.4%
8 13
 
6.4%
7 12
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 194
95.6%
Dash Punctuation 9
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 34
17.5%
2 31
16.0%
3 23
11.9%
5 20
10.3%
0 17
8.8%
6 16
8.2%
4 15
7.7%
9 13
 
6.7%
8 13
 
6.7%
7 12
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 34
16.7%
2 31
15.3%
3 23
11.3%
5 20
9.9%
0 17
8.4%
6 16
7.9%
4 15
7.4%
9 13
 
6.4%
8 13
 
6.4%
7 12
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 34
16.7%
2 31
15.3%
3 23
11.3%
5 20
9.9%
0 17
8.4%
6 16
7.9%
4 15
7.4%
9 13
 
6.4%
8 13
 
6.4%
7 12
 
5.9%

x
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.57257
Minimum126.39501
Maximum129.40881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:05.951836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39501
5-th percentile126.6513
Q1126.91442
median127.09948
Q3128.42836
95-th percentile129.31009
Maximum129.40881
Range3.0137922
Interquartile range (IQR)1.5139372

Descriptive statistics

Standard deviation0.87608235
Coefficient of variation (CV)0.0068673256
Kurtosis-0.77186643
Mean127.57257
Median Absolute Deviation (MAD)0.36978961
Skewness0.81560961
Sum12757.257
Variance0.76752028
MonotonicityNot monotonic
2023-12-10T18:58:06.352299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.986686918406 1
 
1.0%
126.806587243953 1
 
1.0%
129.408806243885 1
 
1.0%
128.664920203188 1
 
1.0%
126.838255027654 1
 
1.0%
129.373397283684 1
 
1.0%
126.91157724762 1
 
1.0%
127.1452862041 1
 
1.0%
127.49036885281 1
 
1.0%
127.581698182563 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.39501400801 1
1.0%
126.435248070616 1
1.0%
126.495934857581 1
1.0%
126.637545060481 1
1.0%
126.649152052779 1
1.0%
126.651410236713 1
1.0%
126.711797037401 1
1.0%
126.718215316989 1
1.0%
126.767513351556 1
1.0%
126.774821552314 1
1.0%
ValueCountFrequency (%)
129.408806243885 1
1.0%
129.373397283684 1
1.0%
129.3671113569 1
1.0%
129.359981598477 1
1.0%
129.343212628423 1
1.0%
129.308344188413 1
1.0%
129.067285776455 1
1.0%
129.058190732261 1
1.0%
129.052759524055 1
1.0%
129.046066320547 1
1.0%

y
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.460846
Minimum33.503345
Maximum38.202916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:06.662450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.503345
5-th percentile34.902008
Q135.220704
median36.756677
Q337.480506
95-th percentile37.76574
Maximum38.202916
Range4.6995712
Interquartile range (IQR)2.2598027

Descriptive statistics

Standard deviation1.1120425
Coefficient of variation (CV)0.030499637
Kurtosis-1.2417554
Mean36.460846
Median Absolute Deviation (MAD)0.81532661
Skewness-0.33808223
Sum3646.0846
Variance1.2366386
MonotonicityNot monotonic
2023-12-10T18:58:06.947438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5568302947234 1
 
1.0%
37.6758178071493 1
 
1.0%
36.9926182389128 1
 
1.0%
38.0879153796583 1
 
1.0%
35.1562312817746 1
 
1.0%
35.6837734315732 1
 
1.0%
37.4083138155857 1
 
1.0%
36.8204766374551 1
 
1.0%
36.0804413696798 1
 
1.0%
36.7850975730425 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.5033448233269 1
1.0%
34.638406265904 1
1.0%
34.7152189200753 1
1.0%
34.7867348842309 1
1.0%
34.8009957746054 1
1.0%
34.9073243900005 1
1.0%
34.9426438905041 1
1.0%
34.9589494953397 1
1.0%
35.0807248790539 1
1.0%
35.0950814591743 1
1.0%
ValueCountFrequency (%)
38.2029160088152 1
1.0%
38.0879153796583 1
1.0%
37.9818421307662 1
1.0%
37.8745174198741 1
1.0%
37.795983403042 1
1.0%
37.7641487642543 1
1.0%
37.7472246815678 1
1.0%
37.6758178071493 1
1.0%
37.6335365562128 1
1.0%
37.6310864857297 1
1.0%

grid_cd
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:58:07.691037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters800
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
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 row다사546509
2nd row마마420301
3rd row마라409772
4th row다사486356
5th row마마639287
ValueCountFrequency (%)
다사546509 1
 
1.0%
라사215861 1
 
1.0%
마아021103 1
 
1.0%
다라397847 1
 
1.0%
마마695446 1
 
1.0%
다사479345 1
 
1.0%
다바683692 1
 
1.0%
다마991870 1
 
1.0%
라바072652 1
 
1.0%
다사630372 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:58:08.542601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 76
9.5%
8 72
 
9.0%
4 70
 
8.8%
2 64
 
8.0%
9 64
 
8.0%
다 63
 
7.9%
3 56
 
7.0%
6 54
 
6.8%
0 49
 
6.1%
7 49
 
6.1%
Other values (7) 183
22.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
75.0%
Other Letter 200
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 76
12.7%
8 72
12.0%
4 70
11.7%
2 64
10.7%
9 64
10.7%
3 56
9.3%
6 54
9.0%
0 49
8.2%
7 49
8.2%
1 46
7.7%
Other Letter
ValueCountFrequency (%)
다 63
31.5%
라 44
22.0%
사 43
21.5%
마 35
17.5%
바 12
 
6.0%
아 2
 
1.0%
나 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 600
75.0%
Hangul 200
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 76
12.7%
8 72
12.0%
4 70
11.7%
2 64
10.7%
9 64
10.7%
3 56
9.3%
6 54
9.0%
0 49
8.2%
7 49
8.2%
1 46
7.7%
Hangul
ValueCountFrequency (%)
다 63
31.5%
라 44
22.0%
사 43
21.5%
마 35
17.5%
바 12
 
6.0%
아 2
 
1.0%
나 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
75.0%
Hangul 200
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 76
12.7%
8 72
12.0%
4 70
11.7%
2 64
10.7%
9 64
10.7%
3 56
9.3%
6 54
9.0%
0 49
8.2%
7 49
8.2%
1 46
7.7%
Hangul
ValueCountFrequency (%)
다 63
31.5%
라 44
22.0%
사 43
21.5%
마 35
17.5%
바 12
 
6.0%
아 2
 
1.0%
나 1
 
0.5%

lst_updt_dt
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210916170801
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210916170801
2nd row20210916170801
3rd row20210916170801
4th row20210916170801
5th row20210916170801

Common Values

ValueCountFrequency (%)
20210916170801 100
100.0%

Length

2023-12-10T18:58:08.854463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:09.062422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210916170801 100
100.0%

data_orgn
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KT
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKT
2nd rowKT
3rd rowKT
4th rowKT
5th rowKT

Common Values

ValueCountFrequency (%)
KT 100
100.0%

Length

2023-12-10T18:58:09.264106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:09.438037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kt 100
100.0%

file_name
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_499_DMSTC_MCST_PRV_PRKLT_2021
100 

Length

Max length32
Median length32
Mean length32
Min length32

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_499_DMSTC_MCST_PRV_PRKLT_2021
2nd rowKC_499_DMSTC_MCST_PRV_PRKLT_2021
3rd rowKC_499_DMSTC_MCST_PRV_PRKLT_2021
4th rowKC_499_DMSTC_MCST_PRV_PRKLT_2021
5th rowKC_499_DMSTC_MCST_PRV_PRKLT_2021

Common Values

ValueCountFrequency (%)
KC_499_DMSTC_MCST_PRV_PRKLT_2021 100
100.0%

Length

2023-12-10T18:58:09.632900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:09.833982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_499_dmstc_mcst_prv_prklt_2021 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210916
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210916
2nd row20210916
3rd row20210916
4th row20210916
5th row20210916

Common Values

ValueCountFrequency (%)
20210916 100
100.0%

Length

2023-12-10T18:58:10.018641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:10.197426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210916 100
100.0%

Sample

idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
0KCDRTPO21N000000001장소교통8276362숭의여자대학교주차장<NA><NA>160302부속주차장1114014200100080003서울특별시중구예장동<NA>8-311140142001114057000111404103215소파로2길10126.98668737.55683다사54650920210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
1KCDRTPO21N000033675장소교통22188673영남알프스국제클라이밍장3주차장<NA><NA>160302부속주차장3171038034105170000울산광역시울주군상북면등억알프스리51731710380343171038000317104853469알프스온천5길103-8129.06728635.557239마마42030120210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
2KCDRTPO21N000000003장소교통10268374신선3동공영주차장<NA><NA>160301공영주차장2620011400101120255부산광역시영도구신선동3가<NA>112-25526200114002620058500262004184159영마루길143129.04606635.080725마라40977220210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
3KCDRTPO21N000000004장소교통10268409공영주차장예술공원노외<NA>160301공영주차장4117110200102400017경기도안양시 만안구석수동<NA>240-1741171102004117159000411714346274예술공원로131번길7126.91977137.418916다사48635620210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
4KCDRTPO21N000000005장소교통10268452신정1동노외공영주차장<NA><NA>160301공영주차장3114010400106350006울산광역시남구신정동<NA>635-631140104003114051000311403170046월평로25129.30834435.541344마마63928720210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
5KCDRTPO21N000000006장소교통10268453제주시공영주차장<NA><NA>160301공영주차장5011010900116110002제주특별자치도제주시용담이동<NA>1611-250110109005011058000501104847444다호북길7126.49593533.503345다다06701720210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
6KCDRTPO21N000000007장소교통10268604백운아트홀주차장2<NA><NA>160302부속주차장4623011000106740000전라남도광양시금호동<NA>67446230110004623055000462303285009금호로215127.72521234.942644라라20560820210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
7KCDRTPO21N000033676장소교통222035935일시장주변노외공영주차장<NA><NA>160301공영주차장4673025021101900001전라남도구례군구례읍봉동리190-1467302502146730250004673046640025일시장작은길20127.47018435.209831다라97290420210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
8KCDRTPO21N000000009장소교통10268696월드컵공원난지천공원주차장<NA><NA>160302부속주차장1144012700115380000서울특별시마포구상암동<NA>153811440127001144074000114403113018월드컵로365126.89248737.567641다사46352220210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
9KCDRTPO21N000000010장소교통10268734마포농수산물시장주차장<NA><NA>160302부속주차장1144012500105330001서울특별시마포구성산동<NA>533-111440125001144073000114403113018월드컵로235126.89773937.56509다사46851920210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
idlclasmlsfcid_poipoi_nmbranch_nmsub_nmmcate_cdmcate_nmpnusido_nmsgg_nmbemd_nmri_nmbeonjibadm_cdhadm_cdrd_cdrd_nmbld_numxygrid_cdlst_updt_dtdata_orgnfile_namebase_ymd
90KCDRTPO21N000000091장소교통13933346SK하이닉스이천본사사원주차장<NA><NA>160302부속주차장4150035026103910015경기도이천시대월면사동리391-1541500350264150035000<NA><NA><NA>127.4880237.246192다사98916320210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
91KCDRTPO21N000000092장소교통13969097청원공설운동장주차장1<NA><NA>160302부속주차장4311425026200510001충청북도청주시 청원구내수읍형동리산51-143114250264311425000431143240027도원세교로369127.55821836.696377라바05255320210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
92KCDRTPO21N000000093장소교통14023971미추홀공원주차장<NA><NA>160302부속주차장2818510600100090001인천광역시연수구송도동<NA>9-128185106002818582000281853152038테크노파크로23126.6514137.381884다사24831720210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
93KCDRTPO21N000000094장소교통14109449고려병원주차빌딩<NA><NA>160302부속주차장4817010400104860001경상남도진주시칠암동<NA>486-148170104004817051500481702332003진주대로868128.09201235.178105라라53987120210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
94KCDRTPO21N000000095장소교통14220806예천천문우주센터주차장<NA><NA>160302부속주차장4790034037100910000경상북도예천군감천면덕율리9147900340374790034000479003307052충효로1078128.50460936.701212라바89756320210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
95KCDRTPO21N000000096장소교통14252552가산동공영주차장<NA><NA>160301공영주차장1154510100101480028서울특별시금천구가산동<NA>148-2811545101001154551000115454151284시흥대로153길53126.89560237.4767다사46542120210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
96KCDRTPO21N000000097장소교통14253577숭의2동제1공영주차장<NA><NA>160301공영주차장2817710100101760005인천광역시미추홀구숭의동<NA>176-528177101002817751000281773000028경인로54126.64915237.464409다사24740920210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
97KCDRTPO21N000000098장소교통14256415대야6공영주차장<NA><NA>160304일반주차장4141010800106610002경기도군포시대야미동<NA>661-241410108004141061000414104400183대야1로11번길14126.91806137.326029다사48425320210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
98KCDRTPO21N000000099장소교통14258103매산유료주차장<NA><NA>160304일반주차장4111513500100260043경기도수원시 팔달구매산로2가<NA>26-4341115135004111566000411154328007갓매산로55번길10127.00392737.269242다사56019020210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916
99KCDRTPO21N000000100장소교통14261462소백유료주차장<NA><NA>160304일반주차장4721010100103290002경상북도영주시영주동<NA>329-247210101004721055000472104727417영주로215번길6128.62373636.826225마바00270320210916170801KTKC_499_DMSTC_MCST_PRV_PRKLT_202120210916