Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory54.4 B

Variable types

Categorical1
Text3
Numeric2

Dataset

Description인천광역시 동구 관내에 위치한 금융기관 현황 데이터로, 행정동명, 지점명, 도로명주소, 전화번호, 위도, 경도의 항목을 게시하고 있습니다.
Author인천광역시 동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15100989&srcSe=7661IVAWM27C61E190

Alerts

경도 is highly overall correlated with 행정동명High correlation
행정동명 is highly overall correlated with 경도High correlation
지점명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 05:31:23.925087
Analysis finished2024-03-13 05:31:24.862940
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
송림6동
7 
송현1·2동
5 
송림2동
4 
만석동
3 
화수1·화평동
3 
Other values (5)
8 

Length

Max length7
Median length4
Mean length4.6666667
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row만석동
2nd row만석동
3rd row만석동
4th row화수1·화평동
5th row화수1·화평동

Common Values

ValueCountFrequency (%)
송림6동 7
23.3%
송현1·2동 5
16.7%
송림2동 4
13.3%
만석동 3
10.0%
화수1·화평동 3
10.0%
화수2동 2
 
6.7%
송림3·5동 2
 
6.7%
송림4동 2
 
6.7%
송현3동 1
 
3.3%
송림1동 1
 
3.3%

Length

2024-03-13T14:31:24.959292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T14:31:25.120350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
송림6동 7
23.3%
송현1·2동 5
16.7%
송림2동 4
13.3%
만석동 3
10.0%
화수1·화평동 3
10.0%
화수2동 2
 
6.7%
송림3·5동 2
 
6.7%
송림4동 2
 
6.7%
송현3동 1
 
3.3%
송림1동 1
 
3.3%

지점명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T14:31:25.349715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.8666667
Min length6

Characters and Unicode

Total characters296
Distinct characters67
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

Unique30 ?
Unique (%)100.0%

Sample

1st row대성신용협동조합
2nd row화도진새마을금고 만석동지점
3rd row동인천신용협동조합
4th row중구농협 화수지점
5th row평화새마을금고 본점
ValueCountFrequency (%)
본점 4
 
7.3%
송현지점 3
 
5.5%
희망새마을금고 3
 
5.5%
새마을금고 3
 
5.5%
송림신협 3
 
5.5%
신한은행 3
 
5.5%
옹진농협 2
 
3.6%
화수지점 2
 
3.6%
평화새마을금고 2
 
3.6%
송림동지점 2
 
3.6%
Other values (28) 28
50.9%
2024-03-13T14:31:25.769572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
8.4%
점 21
 
7.1%
지 17
 
5.7%
송 16
 
5.4%
협 14
 
4.7%
금 13
 
4.4%
신 11
 
3.7%
동 11
 
3.7%
새 11
 
3.7%
마 11
 
3.7%
Other values (57) 146
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 271
91.6%
Space Separator 25
 
8.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 21
 
7.7%
지 17
 
6.3%
송 16
 
5.9%
협 14
 
5.2%
금 13
 
4.8%
신 11
 
4.1%
동 11
 
4.1%
새 11
 
4.1%
마 11
 
4.1%
을 11
 
4.1%
Other values (56) 135
49.8%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 271
91.6%
Common 25
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 21
 
7.7%
지 17
 
6.3%
송 16
 
5.9%
협 14
 
5.2%
금 13
 
4.8%
신 11
 
4.1%
동 11
 
4.1%
새 11
 
4.1%
마 11
 
4.1%
을 11
 
4.1%
Other values (56) 135
49.8%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 271
91.6%
ASCII 25
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
100.0%
Hangul
ValueCountFrequency (%)
점 21
 
7.7%
지 17
 
6.3%
송 16
 
5.9%
협 14
 
5.2%
금 13
 
4.8%
신 11
 
4.1%
동 11
 
4.1%
새 11
 
4.1%
마 11
 
4.1%
을 11
 
4.1%
Other values (56) 135
49.8%

도로명주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T14:31:26.015496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length18.4
Min length14

Characters and Unicode

Total characters552
Distinct characters62
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row인천광역시 동구 석수로 17
2nd row인천광역시 동구 제물량로 397
3rd row인천광역시 동구 화도진로 127
4th row인천광역시 동구 운교로 13-1(화수동)
5th row인천광역시 동구 화도진로 70
ValueCountFrequency (%)
인천광역시 30
23.4%
동구 30
23.4%
화도진로 5
 
3.9%
송림로 4
 
3.1%
1층 3
 
2.3%
화수로 2
 
1.6%
송현로 2
 
1.6%
100 2
 
1.6%
중봉대로 2
 
1.6%
금곡로 2
 
1.6%
Other values (46) 46
35.9%
2024-03-13T14:31:26.494368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
17.8%
동 34
 
6.2%
인 32
 
5.8%
광 30
 
5.4%
역 30
 
5.4%
시 30
 
5.4%
구 30
 
5.4%
로 30
 
5.4%
천 30
 
5.4%
1 26
 
4.7%
Other values (52) 182
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 354
64.1%
Space Separator 98
 
17.8%
Decimal Number 88
 
15.9%
Other Punctuation 4
 
0.7%
Dash Punctuation 4
 
0.7%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 34
 
9.6%
인 32
 
9.0%
광 30
 
8.5%
역 30
 
8.5%
시 30
 
8.5%
구 30
 
8.5%
로 30
 
8.5%
천 30
 
8.5%
송 11
 
3.1%
화 9
 
2.5%
Other values (37) 88
24.9%
Decimal Number
ValueCountFrequency (%)
1 26
29.5%
0 11
12.5%
9 10
 
11.4%
2 8
 
9.1%
8 8
 
9.1%
3 8
 
9.1%
7 8
 
9.1%
6 6
 
6.8%
5 2
 
2.3%
4 1
 
1.1%
Space Separator
ValueCountFrequency (%)
98
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 354
64.1%
Common 198
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 34
 
9.6%
인 32
 
9.0%
광 30
 
8.5%
역 30
 
8.5%
시 30
 
8.5%
구 30
 
8.5%
로 30
 
8.5%
천 30
 
8.5%
송 11
 
3.1%
화 9
 
2.5%
Other values (37) 88
24.9%
Common
ValueCountFrequency (%)
98
49.5%
1 26
 
13.1%
0 11
 
5.6%
9 10
 
5.1%
2 8
 
4.0%
8 8
 
4.0%
3 8
 
4.0%
7 8
 
4.0%
6 6
 
3.0%
, 4
 
2.0%
Other values (5) 11
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 354
64.1%
ASCII 198
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98
49.5%
1 26
 
13.1%
0 11
 
5.6%
9 10
 
5.1%
2 8
 
4.0%
8 8
 
4.0%
3 8
 
4.0%
7 8
 
4.0%
6 6
 
3.0%
, 4
 
2.0%
Other values (5) 11
 
5.6%
Hangul
ValueCountFrequency (%)
동 34
 
9.6%
인 32
 
9.0%
광 30
 
8.5%
역 30
 
8.5%
시 30
 
8.5%
구 30
 
8.5%
로 30
 
8.5%
천 30
 
8.5%
송 11
 
3.1%
화 9
 
2.5%
Other values (37) 88
24.9%

전화번호
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T14:31:26.741366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters360
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

Unique27 ?
Unique (%)90.0%

Sample

1st row032-764-2031
2nd row032-764-6089
3rd row032-764-1300
4th row032-762-9274
5th row032-773-6833
ValueCountFrequency (%)
032-766-7700 3
 
10.0%
032-764-2031 1
 
3.3%
032-763-5051 1
 
3.3%
032-766-7176 1
 
3.3%
032-761-2201 1
 
3.3%
032-763-7614 1
 
3.3%
032-762-6658 1
 
3.3%
032-763-0860 1
 
3.3%
032-764-3351 1
 
3.3%
032-581-0450 1
 
3.3%
Other values (18) 18
60.0%
2024-03-13T14:31:27.071642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 60
16.7%
0 55
15.3%
7 47
13.1%
3 45
12.5%
6 44
12.2%
2 43
11.9%
1 20
 
5.6%
5 15
 
4.2%
4 13
 
3.6%
8 11
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 300
83.3%
Dash Punctuation 60
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
18.3%
7 47
15.7%
3 45
15.0%
6 44
14.7%
2 43
14.3%
1 20
 
6.7%
5 15
 
5.0%
4 13
 
4.3%
8 11
 
3.7%
9 7
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 60
16.7%
0 55
15.3%
7 47
13.1%
3 45
12.5%
6 44
12.2%
2 43
11.9%
1 20
 
5.6%
5 15
 
4.2%
4 13
 
3.6%
8 11
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 60
16.7%
0 55
15.3%
7 47
13.1%
3 45
12.5%
6 44
12.2%
2 43
11.9%
1 20
 
5.6%
5 15
 
4.2%
4 13
 
3.6%
8 11
 
3.1%

위도
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.478726
Minimum37.471217
Maximum37.487921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T14:31:27.235128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.471217
5-th percentile37.473687
Q137.475927
median37.478244
Q337.480361
95-th percentile37.486189
Maximum37.487921
Range0.01670457
Interquartile range (IQR)0.00443409

Descriptive statistics

Standard deviation0.0040330227
Coefficient of variation (CV)0.00010760832
Kurtosis0.19543859
Mean37.478726
Median Absolute Deviation (MAD)0.00227701
Skewness0.63371796
Sum1124.3618
Variance1.6265272 × 10-5
MonotonicityNot monotonic
2024-03-13T14:31:27.347431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
37.48792116 2
 
6.7%
37.48005566 1
 
3.3%
37.47521338 1
 
3.3%
37.4797824 1
 
3.3%
37.476425 1
 
3.3%
37.47823072 1
 
3.3%
37.47747308 1
 
3.3%
37.4761754 1
 
3.3%
37.47584373 1
 
3.3%
37.47577486 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
37.47121659 1
3.3%
37.47340981 1
3.3%
37.47402502 1
3.3%
37.4746417 1
3.3%
37.47521338 1
3.3%
37.475345 1
3.3%
37.47577486 1
3.3%
37.47584373 1
3.3%
37.4761754 1
3.3%
37.4763574 1
3.3%
ValueCountFrequency (%)
37.48792116 2
6.7%
37.4840729 1
3.3%
37.48384651 1
3.3%
37.48378551 1
3.3%
37.482176 1
3.3%
37.4819668 1
3.3%
37.48039775 1
3.3%
37.4802497 1
3.3%
37.48005566 1
3.3%
37.4799745 1
3.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.64037
Minimum126.62593
Maximum126.6591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T14:31:27.514577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.62593
5-th percentile126.62729
Q1126.63462
median126.64316
Q3126.64651
95-th percentile126.65052
Maximum126.6591
Range0.0331729
Interquartile range (IQR)0.01188595

Descriptive statistics

Standard deviation0.0085257192
Coefficient of variation (CV)6.7322284 × 10-5
Kurtosis-0.78145412
Mean126.64037
Median Absolute Deviation (MAD)0.0064602
Skewness-0.091111708
Sum3799.2112
Variance7.2687888 × 10-5
MonotonicityNot monotonic
2024-03-13T14:31:27.678724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
126.647271 2
 
6.7%
126.627367 1
 
3.3%
126.6435452 1
 
3.3%
126.6467619 1
 
3.3%
126.6457436 1
 
3.3%
126.6455075 1
 
3.3%
126.6493492 1
 
3.3%
126.6467604 1
 
3.3%
126.6456739 1
 
3.3%
126.6453329 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
126.6259311 1
3.3%
126.6272216 1
3.3%
126.627367 1
3.3%
126.6285011 1
3.3%
126.6291936 1
3.3%
126.6306723 1
3.3%
126.6317523 1
3.3%
126.634495 1
3.3%
126.634996 1
3.3%
126.6353896 1
3.3%
ValueCountFrequency (%)
126.659104 1
3.3%
126.6514849 1
3.3%
126.6493492 1
3.3%
126.6491655 1
3.3%
126.647271 2
6.7%
126.6467619 1
3.3%
126.6467604 1
3.3%
126.6457436 1
3.3%
126.6456934 1
3.3%
126.6456739 1
3.3%

Interactions

2024-03-13T14:31:24.447515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T14:31:24.218667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T14:31:24.555003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T14:31:24.331060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T14:31:27.796446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명지점명도로명주소전화번호위도경도
행정동명1.0001.0001.0000.6970.5760.794
지점명1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
전화번호0.6971.0001.0001.0000.8970.939
위도0.5761.0001.0000.8971.0000.624
경도0.7941.0001.0000.9390.6241.000
2024-03-13T14:31:27.895125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정동명
위도1.000-0.2510.277
경도-0.2511.0000.507
행정동명0.2770.5071.000

Missing values

2024-03-13T14:31:24.704907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T14:31:24.822838image/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

행정동명지점명도로명주소전화번호위도경도
0만석동대성신용협동조합인천광역시 동구 석수로 17032-764-203137.480056126.627367
1만석동화도진새마을금고 만석동지점인천광역시 동구 제물량로 397032-764-608937.483847126.625931
2만석동동인천신용협동조합인천광역시 동구 화도진로 127032-764-130037.481967126.627222
3화수1·화평동중구농협 화수지점인천광역시 동구 운교로 13-1(화수동)032-762-927437.48025126.628501
4화수1·화평동평화새마을금고 본점인천광역시 동구 화도진로 70032-773-683337.478256126.631752
5화수1·화평동평화새마을금고 화수지점인천광역시 동구 화도진로 102-1032-766-710937.480398126.629194
6화수2동송화 새마을금고인천광역시 동구 화수로69번길 12032-763-678137.484073126.630672
7화수2동송화새마을금고 송현지점인천광역시 동구 화수로 18, 1층 101호032-761-032337.482176126.63539
8송현1·2동송림신협 본점인천광역시 동구 화도진로 29032-765-643337.475345126.634495
9송현1·2동신한은행 송현동지점인천광역시 동구 중봉대로 100 철재기계단지 내032-766-770037.487921126.647271
행정동명지점명도로명주소전화번호위도경도
20송림3·5동희망새마을금고 금송지점인천광역시 동구 금곡로 93032-777-409037.474025126.645693
21송림4동송림 새마을금고인천광역시 동구 송림로162번길 10, 송림파인앤유 상가 1층032-764-708137.477478126.651485
22송림4동우리은행 가좌공단지점인천광역시 동구 봉수대로 85032-581-045037.483786126.659104
23송림6동국민은행 송림동지점인천광역시 동구 송림로 96032-764-335137.475775126.645333
24송림6동농협은행 송림동지점인천광역시 동구 송림로 98032-763-086037.475844126.645674
25송림6동송림중앙신협인천광역시 동구 송림로108032-762-665837.476175126.64676
26송림6동송림신협 재능지점인천광역시 동구 송림로133-1032-763-761437.477473126.649349
27송림6동인천원예농협 본점인천광역시 동구 샛골로174032-761-220137.478231126.645507
28송림6동희망새마을금고 본점인천광역시 동구 송림로 99-2032-766-717637.476425126.645744
29송림6동희망새마을금고 서흥지점인천광역시 동구 인중로680번길 8032-761-119137.479782126.646762