Overview

Dataset statistics

Number of variables8
Number of observations231
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.2 KiB
Average record size in memory67.6 B

Variable types

Numeric3
Text2
Categorical3

Dataset

Description서울특별시 광진구 염화칼슘보관함 위치정보에 대한 데이터로, 광진구 염화칼슘 보관함의 관리번호, 주소, 좌표, 관리기관, 관리부서 등에 대한 정보를 제공합니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15041574/fileData.do

Alerts

관리기관 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with X좌표(GRS80TM) and 1 other fieldsHigh correlation
X좌표(GRS80TM) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
Y좌표(GRS80TM) is highly overall correlated with 관리부서High correlation
관리부서 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 has unique valuesUnique
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:33:24.761375
Analysis finished2024-03-14 12:33:27.333139
Duration2.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct231
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116
Minimum1
Maximum231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-14T21:33:27.465913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.5
Q158.5
median116
Q3173.5
95-th percentile219.5
Maximum231
Range230
Interquartile range (IQR)115

Descriptive statistics

Standard deviation66.828138
Coefficient of variation (CV)0.57610464
Kurtosis-1.2
Mean116
Median Absolute Deviation (MAD)58
Skewness0
Sum26796
Variance4466
MonotonicityStrictly increasing
2024-03-14T21:33:27.748865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
160 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
153 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
Other values (221) 221
95.7%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
231 1
0.4%
230 1
0.4%
229 1
0.4%
228 1
0.4%
227 1
0.4%
226 1
0.4%
225 1
0.4%
224 1
0.4%
223 1
0.4%
222 1
0.4%

관리번호
Text

UNIQUE 

Distinct231
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-03-14T21:33:28.978831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.2727273
Min length4

Characters and Unicode

Total characters1218
Distinct characters23
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

Unique231 ?
Unique (%)100.0%

Sample

1st row중곡1-1
2nd row중곡1-2
3rd row중곡1-3
4th row중곡1-4
5th row중곡1-5
ValueCountFrequency (%)
중곡1-1 1
 
0.4%
광장-16 1
 
0.4%
구의3-8 1
 
0.4%
구의3-9 1
 
0.4%
구의3-10 1
 
0.4%
구의3-11 1
 
0.4%
구의3-12 1
 
0.4%
구의3-13 1
 
0.4%
구의3-14 1
 
0.4%
구의3-15 1
 
0.4%
Other values (221) 221
95.7%
2024-03-14T21:33:30.683381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 231
19.0%
4 120
9.9%
1 103
 
8.5%
중 97
 
8.0%
곡 97
 
8.0%
2 90
 
7.4%
3 64
 
5.3%
구 52
 
4.3%
의 52
 
4.3%
자 48
 
3.9%
Other values (13) 264
21.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 525
43.1%
Other Letter 462
37.9%
Dash Punctuation 231
19.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 97
21.0%
곡 97
21.0%
구 52
11.3%
의 52
11.3%
자 48
10.4%
양 35
 
7.6%
군 19
 
4.1%
광 18
 
3.9%
장 18
 
3.9%
동 10
 
2.2%
Other values (2) 16
 
3.5%
Decimal Number
ValueCountFrequency (%)
4 120
22.9%
1 103
19.6%
2 90
17.1%
3 64
12.2%
5 35
 
6.7%
6 33
 
6.3%
7 27
 
5.1%
8 20
 
3.8%
9 18
 
3.4%
0 15
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 231
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
62.1%
Hangul 462
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 97
21.0%
곡 97
21.0%
구 52
11.3%
의 52
11.3%
자 48
10.4%
양 35
 
7.6%
군 19
 
4.1%
광 18
 
3.9%
장 18
 
3.9%
동 10
 
2.2%
Other values (2) 16
 
3.5%
Common
ValueCountFrequency (%)
- 231
30.6%
4 120
15.9%
1 103
13.6%
2 90
 
11.9%
3 64
 
8.5%
5 35
 
4.6%
6 33
 
4.4%
7 27
 
3.6%
8 20
 
2.6%
9 18
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
62.1%
Hangul 462
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 231
30.6%
4 120
15.9%
1 103
13.6%
2 90
 
11.9%
3 64
 
8.5%
5 35
 
4.6%
6 33
 
4.4%
7 27
 
3.6%
8 20
 
2.6%
9 18
 
2.4%
Hangul
ValueCountFrequency (%)
중 97
21.0%
곡 97
21.0%
구 52
11.3%
의 52
11.3%
자 48
10.4%
양 35
 
7.6%
군 19
 
4.1%
광 18
 
3.9%
장 18
 
3.9%
동 10
 
2.2%
Other values (2) 16
 
3.5%

도로명주소
Text

Distinct230
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-03-14T21:33:31.714367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length19.532468
Min length16

Characters and Unicode

Total characters4512
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)99.1%

Sample

1st row서울특별시 광진구 긴고랑로12길 49
2nd row서울특별시 광진구 면목로 93
3rd row서울특별시 광진구 긴고랑로 12
4th row서울특별시 광진구 긴고랑로1길 31
5th row서울특별시 광진구 천호대로 107길 52
ValueCountFrequency (%)
서울특별시 231
25.1%
광진구 231
25.1%
영화사로9가길 8
 
0.9%
용마산로8가길 7
 
0.8%
31 6
 
0.7%
17 6
 
0.7%
27 6
 
0.7%
49 5
 
0.5%
20 5
 
0.5%
26 5
 
0.5%
Other values (254) 409
44.5%
2024-03-14T21:33:32.914285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
689
15.3%
광 253
 
5.6%
구 237
 
5.3%
서 231
 
5.1%
로 231
 
5.1%
진 231
 
5.1%
울 231
 
5.1%
시 231
 
5.1%
별 231
 
5.1%
특 231
 
5.1%
Other values (53) 1716
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2943
65.2%
Decimal Number 853
 
18.9%
Space Separator 689
 
15.3%
Dash Punctuation 27
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 253
 
8.6%
구 237
 
8.1%
서 231
 
7.8%
로 231
 
7.8%
진 231
 
7.8%
울 231
 
7.8%
시 231
 
7.8%
별 231
 
7.8%
특 231
 
7.8%
길 201
 
6.8%
Other values (41) 635
21.6%
Decimal Number
ValueCountFrequency (%)
2 138
16.2%
1 135
15.8%
3 105
12.3%
4 88
10.3%
6 75
8.8%
8 74
8.7%
5 72
8.4%
7 60
7.0%
9 57
6.7%
0 49
 
5.7%
Space Separator
ValueCountFrequency (%)
689
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2943
65.2%
Common 1569
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 253
 
8.6%
구 237
 
8.1%
서 231
 
7.8%
로 231
 
7.8%
진 231
 
7.8%
울 231
 
7.8%
시 231
 
7.8%
별 231
 
7.8%
특 231
 
7.8%
길 201
 
6.8%
Other values (41) 635
21.6%
Common
ValueCountFrequency (%)
689
43.9%
2 138
 
8.8%
1 135
 
8.6%
3 105
 
6.7%
4 88
 
5.6%
6 75
 
4.8%
8 74
 
4.7%
5 72
 
4.6%
7 60
 
3.8%
9 57
 
3.6%
Other values (2) 76
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2943
65.2%
ASCII 1569
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
689
43.9%
2 138
 
8.8%
1 135
 
8.6%
3 105
 
6.7%
4 88
 
5.6%
6 75
 
4.8%
8 74
 
4.7%
5 72
 
4.6%
7 60
 
3.8%
9 57
 
3.6%
Other values (2) 76
 
4.8%
Hangul
ValueCountFrequency (%)
광 253
 
8.6%
구 237
 
8.1%
서 231
 
7.8%
로 231
 
7.8%
진 231
 
7.8%
울 231
 
7.8%
시 231
 
7.8%
별 231
 
7.8%
특 231
 
7.8%
길 201
 
6.8%
Other values (41) 635
21.6%

X좌표(GRS80TM)
Real number (ℝ)

HIGH CORRELATION 

Distinct220
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.552365
Minimum37.52774
Maximum37.57079
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-14T21:33:33.406680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.52774
5-th percentile37.532385
Q137.54362
median37.55383
Q337.560595
95-th percentile37.568735
Maximum37.57079
Range0.04305
Interquartile range (IQR)0.016975

Descriptive statistics

Standard deviation0.011126053
Coefficient of variation (CV)0.00029628102
Kurtosis-0.72827888
Mean37.552365
Median Absolute Deviation (MAD)0.00732
Skewness-0.36602696
Sum8674.5963
Variance0.00012378906
MonotonicityNot monotonic
2024-03-14T21:33:33.725619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5531 2
 
0.9%
37.55486 2
 
0.9%
37.54671 2
 
0.9%
37.56114 2
 
0.9%
37.55383 2
 
0.9%
37.53758 2
 
0.9%
37.55283 2
 
0.9%
37.56011 2
 
0.9%
37.56193 2
 
0.9%
37.55992 2
 
0.9%
Other values (210) 211
91.3%
ValueCountFrequency (%)
37.52774 1
0.4%
37.52891 1
0.4%
37.52892 1
0.4%
37.52894 1
0.4%
37.52903 1
0.4%
37.53019 1
0.4%
37.53022 1
0.4%
37.53024 1
0.4%
37.53073 1
0.4%
37.53215 1
0.4%
ValueCountFrequency (%)
37.57079 1
0.4%
37.57072 1
0.4%
37.5702 1
0.4%
37.57018 1
0.4%
37.57009 1
0.4%
37.57003 1
0.4%
37.57002 1
0.4%
37.56935 1
0.4%
37.56931 1
0.4%
37.56924 1
0.4%

Y좌표(GRS80TM)
Real number (ℝ)

HIGH CORRELATION 

Distinct159
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.08715
Minimum127.0613
Maximum127.1096
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-14T21:33:33.985197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0613
5-th percentile127.07065
Q1127.08205
median127.0884
Q3127.09335
95-th percentile127.1017
Maximum127.1096
Range0.0483
Interquartile range (IQR)0.0113

Descriptive statistics

Standard deviation0.009230539
Coefficient of variation (CV)7.2631567 × 10-5
Kurtosis0.24374332
Mean127.08715
Median Absolute Deviation (MAD)0.0054
Skewness-0.38463769
Sum29357.132
Variance8.5202851 × 10-5
MonotonicityNot monotonic
2024-03-14T21:33:34.246170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0884 5
 
2.2%
127.0879 5
 
2.2%
127.0882 5
 
2.2%
127.0955 5
 
2.2%
127.0921 4
 
1.7%
127.0957 4
 
1.7%
127.0868 3
 
1.3%
127.0949 3
 
1.3%
127.0937 3
 
1.3%
127.0951 3
 
1.3%
Other values (149) 191
82.7%
ValueCountFrequency (%)
127.0613 1
0.4%
127.0632 1
0.4%
127.0633 1
0.4%
127.0644 2
0.9%
127.0664 1
0.4%
127.0666 1
0.4%
127.067 1
0.4%
127.0679 1
0.4%
127.0693 1
0.4%
127.0703 1
0.4%
ValueCountFrequency (%)
127.1096 1
0.4%
127.1094 1
0.4%
127.1087 1
0.4%
127.1061 1
0.4%
127.106 1
0.4%
127.1054 1
0.4%
127.1052 1
0.4%
127.1049 1
0.4%
127.1041 1
0.4%
127.1031 1
0.4%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
서울특별시 광진구청
231 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 광진구청
2nd row서울특별시 광진구청
3rd row서울특별시 광진구청
4th row서울특별시 광진구청
5th row서울특별시 광진구청

Common Values

ValueCountFrequency (%)
서울특별시 광진구청 231
100.0%

Length

2024-03-14T21:33:34.469051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:33:34.687903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 231
50.0%
광진구청 231
50.0%

관리부서
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
중곡4동
74 
구의2동
25 
구의3동
19 
군자동
19 
광장동
18 
Other values (10)
76 

Length

Max length4
Median length4
Mean length3.7272727
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row중곡1동
2nd row중곡1동
3rd row중곡1동
4th row중곡1동
5th row중곡1동

Common Values

ValueCountFrequency (%)
중곡4동 74
32.0%
구의2동 25
 
10.8%
구의3동 19
 
8.2%
군자동 19
 
8.2%
광장동 18
 
7.8%
자양2동 12
 
5.2%
자양4동 11
 
4.8%
능동 10
 
4.3%
중곡2동 9
 
3.9%
구의1동 8
 
3.5%
Other values (5) 26
 
11.3%

Length

2024-03-14T21:33:34.904046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중곡4동 74
32.0%
구의2동 25
 
10.8%
구의3동 19
 
8.2%
군자동 19
 
8.2%
광장동 18
 
7.8%
자양2동 12
 
5.2%
자양4동 11
 
4.8%
능동 10
 
4.3%
중곡2동 9
 
3.9%
구의1동 8
 
3.5%
Other values (5) 26
 
11.3%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-02-18
231 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-18
2nd row2024-02-18
3rd row2024-02-18
4th row2024-02-18
5th row2024-02-18

Common Values

ValueCountFrequency (%)
2024-02-18 231
100.0%

Length

2024-03-14T21:33:35.125345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:33:35.277749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-18 231
100.0%

Interactions

2024-03-14T21:33:26.448169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:25.048557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:25.768756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:26.674680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:25.279270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:26.002741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:26.821840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:25.522960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:33:26.241371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:33:35.374837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번X좌표(GRS80TM)Y좌표(GRS80TM)관리부서
연번1.0000.8990.8950.970
X좌표(GRS80TM)0.8991.0000.7500.883
Y좌표(GRS80TM)0.8950.7501.0000.895
관리부서0.9700.8830.8951.000
2024-03-14T21:33:35.536010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번X좌표(GRS80TM)Y좌표(GRS80TM)관리부서
연번1.000-0.787-0.1760.797
X좌표(GRS80TM)-0.7871.0000.0730.572
Y좌표(GRS80TM)-0.1760.0731.0000.597
관리부서0.7970.5720.5971.000

Missing values

2024-03-14T21:33:27.026374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:33:27.245540image/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

연번관리번호도로명주소X좌표(GRS80TM)Y좌표(GRS80TM)관리기관관리부서데이터기준일
01중곡1-1서울특별시 광진구 긴고랑로12길 4937.56067127.0799서울특별시 광진구청중곡1동2024-02-18
12중곡1-2서울특별시 광진구 면목로 9337.56193127.0788서울특별시 광진구청중곡1동2024-02-18
23중곡1-3서울특별시 광진구 긴고랑로 1237.56373127.0776서울특별시 광진구청중곡1동2024-02-18
34중곡1-4서울특별시 광진구 긴고랑로1길 3137.56541127.0779서울특별시 광진구청중곡1동2024-02-18
45중곡1-5서울특별시 광진구 천호대로 107길 5237.55992127.0794서울특별시 광진구청중곡1동2024-02-18
56중곡1-6서울특별시 광진구 긴고랑로 4937.56272127.0819서울특별시 광진구청중곡1동2024-02-18
67중곡1-7서울특별시 광진구 면목로 7037.56011127.0781서울특별시 광진구청중곡1동2024-02-18
78중곡2-1서울특별시 광진구 긴고랑로29길 4737.56193127.0863서울특별시 광진구청중곡2동2024-02-18
89중곡2-2서울특별시 광진구 긴고랑로26길 3837.55884127.0846서울특별시 광진구청중곡2동2024-02-18
910중곡2-3서울특별시 광진구 천호대로117길 7237.55812127.0851서울특별시 광진구청중곡2동2024-02-18
연번관리번호도로명주소X좌표(GRS80TM)Y좌표(GRS80TM)관리기관관리부서데이터기준일
221222군자-10서울특별시 광진구 천호대로102길 5537.55669127.0731서울특별시 광진구청군자동2024-02-18
222223군자-11서울특별시 광진구 동일로58길 20-137.55713127.0738서울특별시 광진구청군자동2024-02-18
223224군자-12서울특별시 광진구 동일로56길 4837.55541127.0745서울특별시 광진구청군자동2024-02-18
224225군자-13서울특별시 광진구 면목로 2837.55664127.0762서울특별시 광진구청군자동2024-02-18
225226군자-14서울특별시 광진구 면목로5길 4437.55646127.0736서울특별시 광진구청군자동2024-02-18
226227군자-15서울특별시 광진구 천호대로104나길 15-537.55697127.0755서울특별시 광진구청군자동2024-02-18
227228군자-16서울특별시 광진구 군자로17길 2737.5565127.077서울특별시 광진구청군자동2024-02-18
228229군자-17서울특별시 광진구 면목로 1337.5555127.0756서울특별시 광진구청군자동2024-02-18
229230군자-18서울특별시 광진구 광나루로 38937.54772127.0734서울특별시 광진구청군자동2024-02-18
230231군자-19서울특별시 광진구 동일로 24637.55354127.0704서울특별시 광진구청군자동2024-02-18