Overview

Dataset statistics

Number of variables16
Number of observations1743
Missing cells2584
Missing cells (%)9.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory231.6 KiB
Average record size in memory136.1 B

Variable types

Numeric5
Categorical3
Text8

Dataset

Description경상남도 도로대장전산화 시스템 데이터의 중장기개방계획에 따른 데이터입니다. 시스템 상에서의 각 도로의 유로도로, 터널 등의 정보를 가지고 있으며, 도로대장의 도로점용 데이터를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15091943

Alerts

관리기관 has constant value ""Constant
이력코드 has constant value ""Constant
식별번호 is highly overall correlated with 도로종류High correlation
도로종류 is highly overall correlated with 식별번호High correlation
허가일시(허가번호) has 101 (5.8%) missing valuesMissing
점용면적 has 25 (1.4%) missing valuesMissing
점용_시작일자 has 46 (2.6%) missing valuesMissing
점용_종료일자 has 51 (2.9%) missing valuesMissing
점용시설개요 has 514 (29.5%) missing valuesMissing
지번 has 251 (14.4%) missing valuesMissing
비고 has 1582 (90.8%) missing valuesMissing
점용면적 is highly skewed (γ1 = 29.82553024)Skewed
식별번호 has unique valuesUnique
점용면적 has 418 (24.0%) zerosZeros

Reproduction

Analysis started2023-12-10 22:42:05.617750
Analysis finished2023-12-10 22:42:09.192119
Duration3.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

식별번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1743
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean872
Minimum1
Maximum1743
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T07:42:09.246926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile88.1
Q1436.5
median872
Q31307.5
95-th percentile1655.9
Maximum1743
Range1742
Interquartile range (IQR)871

Descriptive statistics

Standard deviation503.30508
Coefficient of variation (CV)0.57718472
Kurtosis-1.2
Mean872
Median Absolute Deviation (MAD)436
Skewness0
Sum1519896
Variance253316
MonotonicityStrictly increasing
2023-12-11T07:42:09.354173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1160 1
 
0.1%
1171 1
 
0.1%
1170 1
 
0.1%
1169 1
 
0.1%
1168 1
 
0.1%
1167 1
 
0.1%
1166 1
 
0.1%
1165 1
 
0.1%
1164 1
 
0.1%
Other values (1733) 1733
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1743 1
0.1%
1742 1
0.1%
1741 1
0.1%
1740 1
0.1%
1739 1
0.1%
1738 1
0.1%
1737 1
0.1%
1736 1
0.1%
1735 1
0.1%
1734 1
0.1%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
1683
1743 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1683
2nd row1683
3rd row1683
4th row1683
5th row1683

Common Values

ValueCountFrequency (%)
1683 1743
100.0%

Length

2023-12-11T07:42:09.458891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:42:09.532924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1683 1743
100.0%

도로종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
1504
972 
1507
771 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1507
2nd row1507
3rd row1507
4th row1507
5th row1507

Common Values

ValueCountFrequency (%)
1504 972
55.8%
1507 771
44.2%

Length

2023-12-11T07:42:09.621144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:42:09.704292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1504 972
55.8%
1507 771
44.2%

노선번호
Real number (ℝ)

Distinct40
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean896.60585
Minimum30
Maximum1099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T07:42:09.791344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile58
Q11003
median1021
Q31037
95-th percentile1084
Maximum1099
Range1069
Interquartile range (IQR)34

Descriptive statistics

Standard deviation338.91456
Coefficient of variation (CV)0.37799726
Kurtosis2.3416349
Mean896.60585
Median Absolute Deviation (MAD)18
Skewness-2.0678694
Sum1562784
Variance114863.08
MonotonicityNot monotonic
2023-12-11T07:42:09.900729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1021 153
 
8.8%
1022 115
 
6.6%
1080 112
 
6.4%
1018 110
 
6.3%
1077 109
 
6.3%
1001 91
 
5.2%
60 85
 
4.9%
1084 83
 
4.8%
1002 77
 
4.4%
1034 70
 
4.0%
Other values (30) 738
42.3%
ValueCountFrequency (%)
30 56
3.2%
37 13
 
0.7%
58 23
 
1.3%
60 85
4.9%
67 15
 
0.9%
69 49
2.8%
907 6
 
0.3%
1001 91
5.2%
1002 77
4.4%
1003 25
 
1.4%
ValueCountFrequency (%)
1099 10
 
0.6%
1089 44
 
2.5%
1084 83
4.8%
1080 112
6.4%
1077 109
6.3%
1051 8
 
0.5%
1049 6
 
0.3%
1047 12
 
0.7%
1042 32
 
1.8%
1040 19
 
1.1%

구간번호
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.831899
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T07:42:10.003678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q39
95-th percentile14
Maximum16
Range15
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.0061481
Coefficient of variation (CV)0.68693716
Kurtosis-0.39314936
Mean5.831899
Median Absolute Deviation (MAD)3
Skewness0.70817348
Sum10165
Variance16.049223
MonotonicityNot monotonic
2023-12-11T07:42:10.088879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 261
15.0%
4 248
14.2%
7 174
10.0%
9 173
9.9%
2 172
9.9%
3 160
9.2%
6 115
6.6%
5 87
 
5.0%
8 86
 
4.9%
13 77
 
4.4%
Other values (6) 190
10.9%
ValueCountFrequency (%)
1 261
15.0%
2 172
9.9%
3 160
9.2%
4 248
14.2%
5 87
 
5.0%
6 115
6.6%
7 174
10.0%
8 86
 
4.9%
9 173
9.9%
10 11
 
0.6%
ValueCountFrequency (%)
16 18
 
1.0%
15 36
 
2.1%
14 50
 
2.9%
13 77
4.4%
12 36
 
2.1%
11 39
 
2.2%
10 11
 
0.6%
9 173
9.9%
8 86
4.9%
7 174
10.0%

이력코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
0
1743 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1743
100.0%

Length

2023-12-11T07:42:10.187546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:42:10.270627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1743
100.0%

허가일시(허가번호)
Text

MISSING 

Distinct1145
Distinct (%)69.7%
Missing101
Missing (%)5.8%
Memory size13.7 KiB
2023-12-11T07:42:10.476717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length10
Mean length10.03715
Min length10

Characters and Unicode

Total characters16481
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique830 ?
Unique (%)50.5%

Sample

1st row1999-06-25
2nd row1998-04-29
3rd row2000-06-15
4th row2001-08-21
5th row2002-12-17
ValueCountFrequency (%)
1995-04-11 29
 
1.8%
2000-01-01 15
 
0.9%
2007-10-16 6
 
0.4%
2001-11-06 6
 
0.4%
2007-11-09 6
 
0.4%
2007-03-26 5
 
0.3%
2007-07-03 5
 
0.3%
2006-01-01 5
 
0.3%
2005-05-02 5
 
0.3%
2005-05-31 5
 
0.3%
Other values (1135) 1555
94.7%
2023-12-11T07:42:10.782768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4542
27.6%
- 3291
20.0%
2 2204
13.4%
1 2121
12.9%
9 1156
 
7.0%
7 640
 
3.9%
5 608
 
3.7%
6 561
 
3.4%
4 507
 
3.1%
3 496
 
3.0%
Other values (3) 355
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13176
79.9%
Dash Punctuation 3291
 
20.0%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4542
34.5%
2 2204
16.7%
1 2121
16.1%
9 1156
 
8.8%
7 640
 
4.9%
5 608
 
4.6%
6 561
 
4.3%
4 507
 
3.8%
3 496
 
3.8%
8 341
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 3291
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16481
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4542
27.6%
- 3291
20.0%
2 2204
13.4%
1 2121
12.9%
9 1156
 
7.0%
7 640
 
3.9%
5 608
 
3.7%
6 561
 
3.4%
4 507
 
3.1%
3 496
 
3.0%
Other values (3) 355
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16481
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4542
27.6%
- 3291
20.0%
2 2204
13.4%
1 2121
12.9%
9 1156
 
7.0%
7 640
 
3.9%
5 608
 
3.7%
6 561
 
3.4%
4 507
 
3.1%
3 496
 
3.0%
Other values (3) 355
 
2.2%

점용위치
Text

Distinct1645
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2023-12-11T07:42:11.054358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length37
Mean length19.008606
Min length6

Characters and Unicode

Total characters33132
Distinct characters299
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1556 ?
Unique (%)89.3%

Sample

1st row곤명면서정리669-5 외2필지
2nd row곤명면추천리641-1외7
3rd row곤명면 추천리 320-8외 6
4th row곤명면 추천리289-1, 289-5
5th row곤명면 추천리 554-6
ValueCountFrequency (%)
경상남도 256
 
3.7%
함안군 196
 
2.8%
밀양시 168
 
2.4%
고성군 126
 
1.8%
양산시 126
 
1.8%
원동면 114
 
1.6%
거제시 108
 
1.6%
외 81
 
1.2%
합천군 80
 
1.2%
산 75
 
1.1%
Other values (2277) 5603
80.8%
2023-12-11T07:42:11.445251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5230
 
15.8%
리 1775
 
5.4%
1 1586
 
4.8%
- 1521
 
4.6%
면 1505
 
4.5%
2 1051
 
3.2%
3 906
 
2.7%
지 901
 
2.7%
4 756
 
2.3%
산 678
 
2.0%
Other values (289) 17223
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18410
55.6%
Decimal Number 7580
22.9%
Space Separator 5230
 
15.8%
Dash Punctuation 1521
 
4.6%
Other Punctuation 243
 
0.7%
Open Punctuation 54
 
0.2%
Close Punctuation 52
 
0.2%
Math Symbol 37
 
0.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1775
 
9.6%
면 1505
 
8.2%
지 901
 
4.9%
산 678
 
3.7%
외 585
 
3.2%
시 572
 
3.1%
군 563
 
3.1%
필 511
 
2.8%
도 476
 
2.6%
남 427
 
2.3%
Other values (264) 10417
56.6%
Decimal Number
ValueCountFrequency (%)
1 1586
20.9%
2 1051
13.9%
3 906
12.0%
4 756
10.0%
5 661
8.7%
6 627
 
8.3%
7 598
 
7.9%
8 497
 
6.6%
9 451
 
5.9%
0 447
 
5.9%
Other Punctuation
ValueCountFrequency (%)
? 140
57.6%
, 96
39.5%
. 3
 
1.2%
/ 3
 
1.2%
& 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
P 1
20.0%
G 1
20.0%
L 1
20.0%
K 1
20.0%
S 1
20.0%
Space Separator
ValueCountFrequency (%)
5230
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1521
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Math Symbol
ValueCountFrequency (%)
~ 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18410
55.6%
Common 14717
44.4%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1775
 
9.6%
면 1505
 
8.2%
지 901
 
4.9%
산 678
 
3.7%
외 585
 
3.2%
시 572
 
3.1%
군 563
 
3.1%
필 511
 
2.8%
도 476
 
2.6%
남 427
 
2.3%
Other values (264) 10417
56.6%
Common
ValueCountFrequency (%)
5230
35.5%
1 1586
 
10.8%
- 1521
 
10.3%
2 1051
 
7.1%
3 906
 
6.2%
4 756
 
5.1%
5 661
 
4.5%
6 627
 
4.3%
7 598
 
4.1%
8 497
 
3.4%
Other values (10) 1284
 
8.7%
Latin
ValueCountFrequency (%)
P 1
20.0%
G 1
20.0%
L 1
20.0%
K 1
20.0%
S 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18410
55.6%
ASCII 14722
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5230
35.5%
1 1586
 
10.8%
- 1521
 
10.3%
2 1051
 
7.1%
3 906
 
6.2%
4 756
 
5.1%
5 661
 
4.5%
6 627
 
4.3%
7 598
 
4.1%
8 497
 
3.4%
Other values (15) 1289
 
8.8%
Hangul
ValueCountFrequency (%)
리 1775
 
9.6%
면 1505
 
8.2%
지 901
 
4.9%
산 678
 
3.7%
외 585
 
3.2%
시 572
 
3.1%
군 563
 
3.1%
필 511
 
2.8%
도 476
 
2.6%
남 427
 
2.3%
Other values (264) 10417
56.6%

점용목적
Text

Distinct692
Distinct (%)40.0%
Missing13
Missing (%)0.7%
Memory size13.7 KiB
2023-12-11T07:42:11.623047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length7.2635838
Min length2

Characters and Unicode

Total characters12566
Distinct characters314
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique520 ?
Unique (%)30.1%

Sample

1st row진,출입로
2nd row진,출입로
3rd row차량진,출입로
4th row차량진,출입로
5th row차량진출입로
ValueCountFrequency (%)
진출입로 412
 
15.5%
설치 101
 
3.8%
공장 83
 
3.1%
진입로 82
 
3.1%
근린생활시설 70
 
2.6%
신축 67
 
2.5%
건물신축 59
 
2.2%
및 53
 
2.0%
주유소 53
 
2.0%
주택신축 43
 
1.6%
Other values (670) 1629
61.4%
2023-12-11T07:42:11.900714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 927
 
7.4%
921
 
7.3%
진 838
 
6.7%
입 826
 
6.6%
출 698
 
5.6%
설 672
 
5.3%
주 443
 
3.5%
신 295
 
2.3%
장 255
 
2.0%
축 251
 
2.0%
Other values (304) 6440
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11272
89.7%
Space Separator 921
 
7.3%
Other Punctuation 141
 
1.1%
Uppercase Letter 90
 
0.7%
Math Symbol 68
 
0.5%
Decimal Number 26
 
0.2%
Open Punctuation 22
 
0.2%
Close Punctuation 22
 
0.2%
Lowercase Letter 3
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 927
 
8.2%
진 838
 
7.4%
입 826
 
7.3%
출 698
 
6.2%
설 672
 
6.0%
주 443
 
3.9%
신 295
 
2.6%
장 255
 
2.3%
축 251
 
2.2%
치 238
 
2.1%
Other values (268) 5829
51.7%
Uppercase Letter
ValueCountFrequency (%)
C 23
25.6%
P 14
15.6%
V 13
14.4%
T 12
13.3%
E 5
 
5.6%
L 3
 
3.3%
U 3
 
3.3%
G 3
 
3.3%
N 3
 
3.3%
O 3
 
3.3%
Other values (5) 8
 
8.9%
Decimal Number
ValueCountFrequency (%)
2 13
50.0%
1 7
26.9%
4 2
 
7.7%
8 1
 
3.8%
3 1
 
3.8%
0 1
 
3.8%
6 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 64
45.4%
. 47
33.3%
? 17
 
12.1%
· 12
 
8.5%
/ 1
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
v 1
33.3%
c 1
33.3%
p 1
33.3%
Math Symbol
ValueCountFrequency (%)
> 34
50.0%
< 34
50.0%
Space Separator
ValueCountFrequency (%)
921
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11272
89.7%
Common 1201
 
9.6%
Latin 93
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 927
 
8.2%
진 838
 
7.4%
입 826
 
7.3%
출 698
 
6.2%
설 672
 
6.0%
주 443
 
3.9%
신 295
 
2.6%
장 255
 
2.3%
축 251
 
2.2%
치 238
 
2.1%
Other values (268) 5829
51.7%
Common
ValueCountFrequency (%)
921
76.7%
, 64
 
5.3%
. 47
 
3.9%
> 34
 
2.8%
< 34
 
2.8%
( 22
 
1.8%
) 22
 
1.8%
? 17
 
1.4%
2 13
 
1.1%
· 12
 
1.0%
Other values (8) 15
 
1.2%
Latin
ValueCountFrequency (%)
C 23
24.7%
P 14
15.1%
V 13
14.0%
T 12
12.9%
E 5
 
5.4%
L 3
 
3.2%
U 3
 
3.2%
G 3
 
3.2%
N 3
 
3.2%
O 3
 
3.2%
Other values (8) 11
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11271
89.7%
ASCII 1282
 
10.2%
None 12
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 927
 
8.2%
진 838
 
7.4%
입 826
 
7.3%
출 698
 
6.2%
설 672
 
6.0%
주 443
 
3.9%
신 295
 
2.6%
장 255
 
2.3%
축 251
 
2.2%
치 238
 
2.1%
Other values (267) 5828
51.7%
ASCII
ValueCountFrequency (%)
921
71.8%
, 64
 
5.0%
. 47
 
3.7%
> 34
 
2.7%
< 34
 
2.7%
C 23
 
1.8%
( 22
 
1.7%
) 22
 
1.7%
? 17
 
1.3%
P 14
 
1.1%
Other values (25) 84
 
6.6%
None
ValueCountFrequency (%)
· 12
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

점용면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct572
Distinct (%)33.3%
Missing25
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean207.24221
Minimum0
Maximum35169
Zeros418
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T07:42:12.234437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median40
Q3247
95-th percentile679.15
Maximum35169
Range35169
Interquartile range (IQR)246

Descriptive statistics

Standard deviation951.90611
Coefficient of variation (CV)4.5932058
Kurtosis1067.6418
Mean207.24221
Median Absolute Deviation (MAD)40
Skewness29.82553
Sum356042.12
Variance906125.25
MonotonicityNot monotonic
2023-12-11T07:42:12.342285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 418
 
24.0%
1.0 52
 
3.0%
2.0 29
 
1.7%
20.0 19
 
1.1%
10.0 17
 
1.0%
30.0 15
 
0.9%
8.0 13
 
0.7%
35.0 12
 
0.7%
40.0 11
 
0.6%
33.0 10
 
0.6%
Other values (562) 1122
64.4%
(Missing) 25
 
1.4%
ValueCountFrequency (%)
0.0 418
24.0%
0.12 1
 
0.1%
0.2 1
 
0.1%
0.25 1
 
0.1%
0.3 1
 
0.1%
0.4 1
 
0.1%
0.6 1
 
0.1%
0.82 2
 
0.1%
0.88 1
 
0.1%
1.0 52
 
3.0%
ValueCountFrequency (%)
35169.0 1
0.1%
9684.0 1
0.1%
5137.0 1
0.1%
4811.0 1
0.1%
4182.0 1
0.1%
4169.0 1
0.1%
3134.0 1
0.1%
3064.0 1
0.1%
3053.0 1
0.1%
2554.0 1
0.1%

점용_시작일자
Text

MISSING 

Distinct1154
Distinct (%)68.0%
Missing46
Missing (%)2.6%
Memory size13.7 KiB
2023-12-11T07:42:12.554332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.95934
Min length2

Characters and Unicode

Total characters16901
Distinct characters29
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique816 ?
Unique (%)48.1%

Sample

1st row1999-06-26
2nd row1998-04-29
3rd row2000-06-01
4th row2001-08-01
5th row2002-12-01
ValueCountFrequency (%)
1995-04-11 27
 
1.6%
2008-01-01 17
 
1.0%
2004-01-01 13
 
0.8%
2000-01-01 11
 
0.6%
2001-01-01 7
 
0.4%
2007-01-01 7
 
0.4%
2006-01-01 7
 
0.4%
2001-11-06 6
 
0.4%
2005-06-02 5
 
0.3%
2004-07-15 5
 
0.3%
Other values (1144) 1592
93.8%
2023-12-11T07:42:12.896129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4725
28.0%
- 3377
20.0%
2 2254
13.3%
1 2196
13.0%
9 1136
 
6.7%
7 637
 
3.8%
5 602
 
3.6%
6 563
 
3.3%
4 517
 
3.1%
3 493
 
2.9%
Other values (19) 401
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13481
79.8%
Dash Punctuation 3377
 
20.0%
Lowercase Letter 26
 
0.2%
Uppercase Letter 13
 
0.1%
Other Letter 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 6
23.1%
a 5
19.2%
n 4
15.4%
y 3
11.5%
r 2
 
7.7%
o 1
 
3.8%
v 1
 
3.8%
g 1
 
3.8%
e 1
 
3.8%
b 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
0 4725
35.0%
2 2254
16.7%
1 2196
16.3%
9 1136
 
8.4%
7 637
 
4.7%
5 602
 
4.5%
6 563
 
4.2%
4 517
 
3.8%
3 493
 
3.7%
8 358
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
J 5
38.5%
M 5
38.5%
N 1
 
7.7%
A 1
 
7.7%
F 1
 
7.7%
Other Letter
ValueCountFrequency (%)
구 2
50.0%
영 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 3377
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16858
99.7%
Latin 39
 
0.2%
Hangul 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 6
15.4%
J 5
12.8%
a 5
12.8%
M 5
12.8%
n 4
10.3%
y 3
7.7%
r 2
 
5.1%
N 1
 
2.6%
o 1
 
2.6%
v 1
 
2.6%
Other values (6) 6
15.4%
Common
ValueCountFrequency (%)
0 4725
28.0%
- 3377
20.0%
2 2254
13.4%
1 2196
13.0%
9 1136
 
6.7%
7 637
 
3.8%
5 602
 
3.6%
6 563
 
3.3%
4 517
 
3.1%
3 493
 
2.9%
Hangul
ValueCountFrequency (%)
구 2
50.0%
영 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16897
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4725
28.0%
- 3377
20.0%
2 2254
13.3%
1 2196
13.0%
9 1136
 
6.7%
7 637
 
3.8%
5 602
 
3.6%
6 563
 
3.3%
4 517
 
3.1%
3 493
 
2.9%
Other values (17) 397
 
2.3%
Hangul
ValueCountFrequency (%)
구 2
50.0%
영 2
50.0%

점용_종료일자
Text

MISSING 

Distinct916
Distinct (%)54.1%
Missing51
Missing (%)2.9%
Memory size13.7 KiB
2023-12-11T07:42:13.112366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9899527
Min length2

Characters and Unicode

Total characters16903
Distinct characters13
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

Unique681 ?
Unique (%)40.2%

Sample

1st row2009-05-31
2nd row2008-04-28
3rd row2001-05-30
4th row2006-07-30
5th row2007-11-30
ValueCountFrequency (%)
2016-12-31 90
 
5.3%
2015-12-31 54
 
3.2%
2017-12-31 46
 
2.7%
2014-12-31 41
 
2.4%
2010-12-31 41
 
2.4%
2013-12-31 32
 
1.9%
2008-12-31 31
 
1.8%
2012-12-31 25
 
1.5%
2005-04-10 24
 
1.4%
2011-12-31 21
 
1.2%
Other values (906) 1287
76.1%
2023-12-11T07:42:13.438729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3750
22.2%
1 3406
20.2%
- 3380
20.0%
2 2863
16.9%
3 957
 
5.7%
5 511
 
3.0%
6 506
 
3.0%
7 492
 
2.9%
4 430
 
2.5%
8 304
 
1.8%
Other values (3) 304
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13519
80.0%
Dash Punctuation 3380
 
20.0%
Other Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3750
27.7%
1 3406
25.2%
2 2863
21.2%
3 957
 
7.1%
5 511
 
3.8%
6 506
 
3.7%
7 492
 
3.6%
4 430
 
3.2%
8 304
 
2.2%
9 300
 
2.2%
Other Letter
ValueCountFrequency (%)
영 2
50.0%
구 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 3380
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16899
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3750
22.2%
1 3406
20.2%
- 3380
20.0%
2 2863
16.9%
3 957
 
5.7%
5 511
 
3.0%
6 506
 
3.0%
7 492
 
2.9%
4 430
 
2.5%
8 304
 
1.8%
Hangul
ValueCountFrequency (%)
영 2
50.0%
구 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16899
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3750
22.2%
1 3406
20.2%
- 3380
20.0%
2 2863
16.9%
3 957
 
5.7%
5 511
 
3.0%
6 506
 
3.0%
7 492
 
2.9%
4 430
 
2.5%
8 304
 
1.8%
Hangul
ValueCountFrequency (%)
영 2
50.0%
구 2
50.0%

점용시설개요
Text

MISSING 

Distinct222
Distinct (%)18.1%
Missing514
Missing (%)29.5%
Memory size13.7 KiB
2023-12-11T07:42:13.632484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length5.0976404
Min length1

Characters and Unicode

Total characters6265
Distinct characters214
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)12.1%

Sample

1st row진.출입로
2nd row진.출입로
3rd row진.출입로
4th row진.출입로
5th row진.출입로
ValueCountFrequency (%)
진출입로 424
28.5%
진·출입로 125
 
8.4%
콘크리트 107
 
7.2%
포장 93
 
6.2%
진.출입로 62
 
4.2%
포 40
 
2.7%
차량 39
 
2.6%
진출입 38
 
2.6%
콘크리트포장 37
 
2.5%
아스콘 34
 
2.3%
Other values (224) 490
32.9%
2023-12-11T07:42:13.933748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
진 714
 
11.4%
입 704
 
11.2%
출 688
 
11.0%
로 678
 
10.8%
260
 
4.2%
콘 202
 
3.2%
포 201
 
3.2%
장 170
 
2.7%
리 155
 
2.5%
트 152
 
2.4%
Other values (204) 2341
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5560
88.7%
Space Separator 260
 
4.2%
Other Punctuation 232
 
3.7%
Decimal Number 117
 
1.9%
Uppercase Letter 49
 
0.8%
Lowercase Letter 20
 
0.3%
Math Symbol 11
 
0.2%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 714
12.8%
입 704
12.7%
출 688
 
12.4%
로 678
 
12.2%
콘 202
 
3.6%
포 201
 
3.6%
장 170
 
3.1%
리 155
 
2.8%
트 152
 
2.7%
크 152
 
2.7%
Other values (168) 1744
31.4%
Uppercase Letter
ValueCountFrequency (%)
L 15
30.6%
C 10
20.4%
U 5
 
10.2%
V 4
 
8.2%
T 4
 
8.2%
P 2
 
4.1%
O 2
 
4.1%
N 2
 
4.1%
D 2
 
4.1%
J 1
 
2.0%
Other values (2) 2
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 30
25.6%
0 22
18.8%
2 13
11.1%
4 12
 
10.3%
3 10
 
8.5%
6 9
 
7.7%
7 8
 
6.8%
5 7
 
6.0%
8 3
 
2.6%
9 3
 
2.6%
Other Punctuation
ValueCountFrequency (%)
· 127
54.7%
. 71
30.6%
, 29
 
12.5%
? 4
 
1.7%
/ 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
m 16
80.0%
φ 3
 
15.0%
a 1
 
5.0%
Space Separator
ValueCountFrequency (%)
260
100.0%
Math Symbol
ValueCountFrequency (%)
= 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5560
88.7%
Common 636
 
10.2%
Latin 66
 
1.1%
Greek 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 714
12.8%
입 704
12.7%
출 688
 
12.4%
로 678
 
12.2%
콘 202
 
3.6%
포 201
 
3.6%
장 170
 
3.1%
리 155
 
2.8%
트 152
 
2.7%
크 152
 
2.7%
Other values (168) 1744
31.4%
Common
ValueCountFrequency (%)
260
40.9%
· 127
20.0%
. 71
 
11.2%
1 30
 
4.7%
, 29
 
4.6%
0 22
 
3.5%
2 13
 
2.0%
4 12
 
1.9%
= 11
 
1.7%
3 10
 
1.6%
Other values (11) 51
 
8.0%
Latin
ValueCountFrequency (%)
m 16
24.2%
L 15
22.7%
C 10
15.2%
U 5
 
7.6%
V 4
 
6.1%
T 4
 
6.1%
P 2
 
3.0%
O 2
 
3.0%
N 2
 
3.0%
D 2
 
3.0%
Other values (4) 4
 
6.1%
Greek
ValueCountFrequency (%)
φ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5560
88.7%
ASCII 573
 
9.1%
None 130
 
2.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
진 714
12.8%
입 704
12.7%
출 688
 
12.4%
로 678
 
12.2%
콘 202
 
3.6%
포 201
 
3.6%
장 170
 
3.1%
리 155
 
2.8%
트 152
 
2.7%
크 152
 
2.7%
Other values (168) 1744
31.4%
ASCII
ValueCountFrequency (%)
260
45.4%
. 71
 
12.4%
1 30
 
5.2%
, 29
 
5.1%
0 22
 
3.8%
m 16
 
2.8%
L 15
 
2.6%
2 13
 
2.3%
4 12
 
2.1%
= 11
 
1.9%
Other values (23) 94
 
16.4%
None
ValueCountFrequency (%)
· 127
97.7%
φ 3
 
2.3%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

법정동코드
Real number (ℝ)

Distinct493
Distinct (%)28.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean4.8592081 × 109
Minimum4.811025 × 109
Maximum4.889046 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T07:42:14.048966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.811025 × 109
5-th percentile4.822034 × 109
Q14.831032 × 109
median4.8730355 × 109
Q34.885031 × 109
95-th percentile4.888041 × 109
Maximum4.889046 × 109
Range78021002
Interquartile range (IQR)53999004

Descriptive statistics

Standard deviation27199094
Coefficient of variation (CV)0.0055974334
Kurtosis-1.6411778
Mean4.8592081 × 109
Median Absolute Deviation (MAD)13997502
Skewness-0.37469927
Sum8.4647405 × 1012
Variance7.397907 × 1014
MonotonicityNot monotonic
2023-12-11T07:42:14.163673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4833032026 23
 
1.3%
4833032022 23
 
1.3%
4873032030 22
 
1.3%
4833032021 20
 
1.1%
4874034032 19
 
1.1%
4827035030 18
 
1.0%
4827035029 18
 
1.0%
4873034021 18
 
1.0%
4827038021 17
 
1.0%
4874042030 17
 
1.0%
Other values (483) 1547
88.8%
ValueCountFrequency (%)
4811025027 4
0.2%
4811025028 6
0.3%
4811025029 2
 
0.1%
4811025032 1
 
0.1%
4811025033 6
0.3%
4811025034 3
0.2%
4811025036 5
0.3%
4811025037 2
 
0.1%
4811025038 4
0.2%
4811025039 3
0.2%
ValueCountFrequency (%)
4889046029 2
 
0.1%
4889045027 1
 
0.1%
4889045026 1
 
0.1%
4889045025 1
 
0.1%
4889045023 7
0.4%
4889045022 1
 
0.1%
4889044028 5
0.3%
4889044027 1
 
0.1%
4889044026 3
0.2%
4889044022 1
 
0.1%

지번
Text

MISSING 

Distinct1300
Distinct (%)87.1%
Missing251
Missing (%)14.4%
Memory size13.7 KiB
2023-12-11T07:42:14.443433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1233244
Min length1

Characters and Unicode

Total characters7644
Distinct characters40
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1145 ?
Unique (%)76.7%

Sample

1st row669-5
2nd row641-1
3rd row320-8
4th row289-1
5th row554-6
ValueCountFrequency (%)
도 19
 
1.2%
1 10
 
0.6%
01월 10
 
0.6%
02월 8
 
0.5%
03월 7
 
0.4%
02일 7
 
0.4%
01일 7
 
0.4%
mar-80 5
 
0.3%
10월 5
 
0.3%
07월 5
 
0.3%
Other values (1280) 1479
94.7%
2023-12-11T07:42:14.833761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1231
16.1%
1 1127
14.7%
2 813
10.6%
3 644
8.4%
4 565
7.4%
5 521
6.8%
6 510
6.7%
7 475
 
6.2%
0 421
 
5.5%
8 399
 
5.2%
Other values (30) 938
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5828
76.2%
Dash Punctuation 1231
 
16.1%
Other Letter 229
 
3.0%
Lowercase Letter 186
 
2.4%
Uppercase Letter 93
 
1.2%
Space Separator 74
 
1.0%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 44
23.7%
r 31
16.7%
n 21
11.3%
e 17
 
9.1%
u 16
 
8.6%
p 15
 
8.1%
b 14
 
7.5%
l 10
 
5.4%
y 6
 
3.2%
g 4
 
2.2%
Other values (4) 8
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 1127
19.3%
2 813
13.9%
3 644
11.1%
4 565
9.7%
5 521
8.9%
6 510
8.8%
7 475
8.2%
0 421
 
7.2%
8 399
 
6.8%
9 353
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
J 31
33.3%
M 25
26.9%
A 16
17.2%
F 14
15.1%
S 3
 
3.2%
O 2
 
2.2%
N 2
 
2.2%
Other Letter
ValueCountFrequency (%)
산 106
46.3%
월 49
21.4%
일 49
21.4%
도 22
 
9.6%
번 2
 
0.9%
지 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 1231
100.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7136
93.4%
Latin 279
 
3.6%
Hangul 229
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 44
15.8%
r 31
11.1%
J 31
11.1%
M 25
9.0%
n 21
7.5%
e 17
 
6.1%
u 16
 
5.7%
A 16
 
5.7%
p 15
 
5.4%
F 14
 
5.0%
Other values (11) 49
17.6%
Common
ValueCountFrequency (%)
- 1231
17.3%
1 1127
15.8%
2 813
11.4%
3 644
9.0%
4 565
7.9%
5 521
7.3%
6 510
7.1%
7 475
 
6.7%
0 421
 
5.9%
8 399
 
5.6%
Other values (3) 430
 
6.0%
Hangul
ValueCountFrequency (%)
산 106
46.3%
월 49
21.4%
일 49
21.4%
도 22
 
9.6%
번 2
 
0.9%
지 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7415
97.0%
Hangul 229
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1231
16.6%
1 1127
15.2%
2 813
11.0%
3 644
8.7%
4 565
7.6%
5 521
7.0%
6 510
6.9%
7 475
 
6.4%
0 421
 
5.7%
8 399
 
5.4%
Other values (24) 709
9.6%
Hangul
ValueCountFrequency (%)
산 106
46.3%
월 49
21.4%
일 49
21.4%
도 22
 
9.6%
번 2
 
0.9%
지 1
 
0.4%

비고
Text

MISSING 

Distinct108
Distinct (%)67.1%
Missing1582
Missing (%)90.8%
Memory size13.7 KiB
2023-12-11T07:42:15.073627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length24
Mean length7.0248447
Min length1

Characters and Unicode

Total characters1131
Distinct characters133
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)58.4%

Sample

1st row0.2m, 796.5m
2nd row1개소
3rd row6본
4th row1개소
5th row2개소
ValueCountFrequency (%)
본 13
 
5.6%
설치 13
 
5.6%
점용기간갱신 11
 
4.7%
m 9
 
3.9%
1본 9
 
3.9%
진,출입로 8
 
3.4%
매설 7
 
3.0%
1개소 5
 
2.1%
2본 3
 
1.3%
축사 3
 
1.3%
Other values (134) 152
65.2%
2023-12-11T07:42:15.425603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 73
 
6.5%
72
 
6.4%
0 58
 
5.1%
본 45
 
4.0%
m 41
 
3.6%
= 38
 
3.4%
2 35
 
3.1%
L 34
 
3.0%
3 32
 
2.8%
a 30
 
2.7%
Other values (123) 673
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 430
38.0%
Decimal Number 297
26.3%
Lowercase Letter 103
 
9.1%
Uppercase Letter 85
 
7.5%
Space Separator 72
 
6.4%
Other Punctuation 67
 
5.9%
Math Symbol 39
 
3.4%
Close Punctuation 12
 
1.1%
Open Punctuation 12
 
1.1%
Other Symbol 9
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
본 45
 
10.5%
설 22
 
5.1%
신 21
 
4.9%
로 16
 
3.7%
용 16
 
3.7%
주 14
 
3.3%
기 14
 
3.3%
소 13
 
3.0%
치 13
 
3.0%
점 12
 
2.8%
Other values (84) 244
56.7%
Uppercase Letter
ValueCountFrequency (%)
L 34
40.0%
M 26
30.6%
C 5
 
5.9%
K 4
 
4.7%
B 3
 
3.5%
A 3
 
3.5%
D 3
 
3.5%
T 3
 
3.5%
V 2
 
2.4%
G 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 73
24.6%
0 58
19.5%
2 35
11.8%
3 32
10.8%
5 22
 
7.4%
4 20
 
6.7%
6 19
 
6.4%
7 16
 
5.4%
9 14
 
4.7%
8 8
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
m 41
39.8%
a 30
29.1%
r 15
 
14.6%
e 15
 
14.6%
v 1
 
1.0%
o 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 24
35.8%
. 22
32.8%
: 18
26.9%
? 2
 
3.0%
/ 1
 
1.5%
Math Symbol
ValueCountFrequency (%)
= 38
97.4%
∮ 1
 
2.6%
Space Separator
ValueCountFrequency (%)
72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 513
45.4%
Hangul 430
38.0%
Latin 188
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
본 45
 
10.5%
설 22
 
5.1%
신 21
 
4.9%
로 16
 
3.7%
용 16
 
3.7%
주 14
 
3.3%
기 14
 
3.3%
소 13
 
3.0%
치 13
 
3.0%
점 12
 
2.8%
Other values (84) 244
56.7%
Common
ValueCountFrequency (%)
1 73
14.2%
72
14.0%
0 58
11.3%
= 38
 
7.4%
2 35
 
6.8%
3 32
 
6.2%
, 24
 
4.7%
. 22
 
4.3%
5 22
 
4.3%
4 20
 
3.9%
Other values (12) 117
22.8%
Latin
ValueCountFrequency (%)
m 41
21.8%
L 34
18.1%
a 30
16.0%
M 26
13.8%
r 15
 
8.0%
e 15
 
8.0%
C 5
 
2.7%
K 4
 
2.1%
B 3
 
1.6%
A 3
 
1.6%
Other values (7) 12
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 691
61.1%
Hangul 430
38.0%
CJK Compat 9
 
0.8%
Math Operators 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 73
 
10.6%
72
 
10.4%
0 58
 
8.4%
m 41
 
5.9%
= 38
 
5.5%
2 35
 
5.1%
L 34
 
4.9%
3 32
 
4.6%
a 30
 
4.3%
M 26
 
3.8%
Other values (27) 252
36.5%
Hangul
ValueCountFrequency (%)
본 45
 
10.5%
설 22
 
5.1%
신 21
 
4.9%
로 16
 
3.7%
용 16
 
3.7%
주 14
 
3.3%
기 14
 
3.3%
소 13
 
3.0%
치 13
 
3.0%
점 12
 
2.8%
Other values (84) 244
56.7%
CJK Compat
ValueCountFrequency (%)
㎡ 9
100.0%
Math Operators
ValueCountFrequency (%)
∮ 1
100.0%

Interactions

2023-12-11T07:42:08.372359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:06.511426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:06.933575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.567923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.981460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.453874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:06.587758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.026640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.650612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.068141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.533321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:06.660538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.112881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.728565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.139255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.617452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:06.736863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.211869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.811057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.216794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.693733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:06.826211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.289891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:07.893779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:42:08.292542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:42:15.501768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식별번호도로종류노선번호구간번호점용면적법정동코드
식별번호1.0000.9440.7220.6210.0290.606
도로종류0.9441.0000.2810.2080.0000.666
노선번호0.7220.2811.0000.2560.0000.336
구간번호0.6210.2080.2561.0000.0000.552
점용면적0.0290.0000.0000.0001.0000.000
법정동코드0.6060.6660.3360.5520.0001.000
2023-12-11T07:42:15.583493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식별번호노선번호구간번호점용면적법정동코드도로종류
식별번호1.0000.408-0.0020.1350.0020.797
노선번호0.4081.000-0.0470.0200.0570.455
구간번호-0.002-0.0471.0000.0160.0520.162
점용면적0.1350.0200.0161.000-0.1800.000
법정동코드0.0020.0570.052-0.1801.0000.486
도로종류0.7970.4550.1620.0000.4861.000

Missing values

2023-12-11T07:42:08.809913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:42:08.979600image/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.
2023-12-11T07:42:09.108004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

식별번호관리기관도로종류노선번호구간번호이력코드허가일시(허가번호)점용위치점용목적점용면적점용_시작일자점용_종료일자점용시설개요법정동코드지번비고
011683150758201999-06-25곤명면서정리669-5 외2필지진,출입로90.01999-06-262009-05-31진.출입로4824035023669-5<NA>
121683150758201998-04-29곤명면추천리641-1외7진,출입로231.01998-04-292008-04-28진.출입로4824036021641-1<NA>
231683150758202000-06-15곤명면 추천리 320-8외 6차량진,출입로314.02000-06-012001-05-30진.출입로4824036021320-8<NA>
341683150758202001-08-21곤명면 추천리289-1, 289-5차량진,출입로480.02001-08-012006-07-30진.출입로4824036021289-1<NA>
451683150758202002-12-17곤명면 추천리 554-6차량진출입로276.02002-12-012007-11-30진.출입로4824036021554-6<NA>
561683150758202002-11-13서포면 구평리 560-7차량진출입로8.02002-11-012007-10-30진.출입로4824037027560-7<NA>
671683150758202002-04-17곤명면추천리289-1,289-5차량진출입로480.02001-08-012006-07-30진.출입로4824036021289-1<NA>
781683150758202003-04-07서포면 외구리164-4외1필지차량진.출입로개설187.02003-04-012013-03-30진.출입로4824037023164-4<NA>
891683150758202003-03-03서포면구랑리783-1외1필지차량진.출입로개설185.02003-03-012008-02-28진.출입로4824037025783-1<NA>
9101683150758202003-02-10서포면구평리산49-1번지외1필지차량진.출입로개설148.02003-02-012008-01-30진.출입로4824037027산49-1<NA>
식별번호관리기관도로종류노선번호구간번호이력코드허가일시(허가번호)점용위치점용목적점용면적점용_시작일자점용_종료일자점용시설개요법정동코드지번비고
17331734168315041084602005-12-27가조면 도리 1464-2방범용 CCTV 설치0.822005-12-272014-12-31<NA>48880400261464-2축사 진,출입로 설치
17341735168315041084602000-08-17가조면 장기리 일원급수지역 확대공사에 따른 수도관 매설711.02000-08-172009-12-31<NA>4888040026<NA>통신관로 매설
17351736168315041084802005-06-13합천군 가야면 야천리 449-1전주 설치9.02005-06-132015-06-12<NA>4889033032449-1<NA>
17361737168315041084802005-08-05합천군 가야면 매안리 592-7외 1필지진입로181.02005-08-052015-08-04<NA>4889033026592-7<NA>
17371738168315041084802004-10-25합천군 가야면 매안리 631-14농산물창고 진출입로45.02004-10-252014-10-24<NA>4889033026631-14<NA>
17381739168315041084902006-12-18합천군 야로면 하림리 352-5통신주 설치1.82006-12-182016-12-17<NA>4889034031352-5<NA>
17391740168315041084902002-01-12합천군 야로면 야로리 381-5자연휴양림 안내표지판<NA>2002-01-122012-01-11<NA>4889034030381-5<NA>
17401741168315041084901999-04-23합천군 야로면 정대리생활용수 관로 매설18.71999-04-232009-04-22<NA>4889034023<NA><NA>
17411742168315041084902001-11-23합천군 야로면 매촌리전주 설치1.22001-11-232011-11-22<NA>4889034029<NA><NA>
17421743168315041084901998-10-26합천군 야로면 덕암리 정대리전주설치1.761998-10-262008-10-25<NA>4889034021<NA><NA>