Overview

Dataset statistics

Number of variables5
Number of observations1204
Missing cells5815
Missing cells (%)96.6%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory49.5 KiB
Average record size in memory42.1 B

Variable types

Text3
Numeric2

Dataset

Description인천광역시 연수구 관내에 있는 은행 등 금융 시설에 대한 데이터 입니다.은행명, 위치(주소), 전화번호 항목을 제공합니다.
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15039688&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
금융기관명 has 1163 (96.6%) missing valuesMissing
주소 has 1163 (96.6%) missing valuesMissing
위도 has 1163 (96.6%) missing valuesMissing
경도 has 1163 (96.6%) missing valuesMissing
전화번호 has 1163 (96.6%) missing valuesMissing

Reproduction

Analysis started2024-01-28 07:52:27.927904
Analysis finished2024-01-28 07:52:28.752119
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

금융기관명
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing1163
Missing (%)96.6%
Memory size9.5 KiB
2024-01-28T16:52:28.889953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.609756
Min length4

Characters and Unicode

Total characters435
Distinct characters94
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row경인북부수협 선학지점
2nd row관교문학새마을금고 제2분소
3rd row국민은행 송도지점
4th row국민은행동춘동지점
5th row국민은행송도PB센터
ValueCountFrequency (%)
송도지점 9
 
13.6%
송도신도시지점 6
 
9.1%
신한은행 3
 
4.5%
우리은행 3
 
4.5%
농협중앙회 2
 
3.0%
옥련동지점 2
 
3.0%
남인천농협 2
 
3.0%
선학지점 2
 
3.0%
인평신협 1
 
1.5%
외환은행 1
 
1.5%
Other values (35) 35
53.0%
2024-01-28T16:52:29.195381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 33
 
7.6%
지 32
 
7.4%
도 27
 
6.2%
25
 
5.7%
송 21
 
4.8%
은 19
 
4.4%
행 19
 
4.4%
협 15
 
3.4%
신 12
 
2.8%
동 11
 
2.5%
Other values (84) 221
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 401
92.2%
Space Separator 25
 
5.7%
Uppercase Letter 6
 
1.4%
Decimal Number 1
 
0.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 33
 
8.2%
지 32
 
8.0%
도 27
 
6.7%
송 21
 
5.2%
은 19
 
4.7%
행 19
 
4.7%
협 15
 
3.7%
신 12
 
3.0%
동 11
 
2.7%
인 10
 
2.5%
Other values (75) 202
50.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
33.3%
C 1
16.7%
P 1
16.7%
S 1
16.7%
K 1
16.7%
Space Separator
ValueCountFrequency (%)
25
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 401
92.2%
Common 28
 
6.4%
Latin 6
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 33
 
8.2%
지 32
 
8.0%
도 27
 
6.7%
송 21
 
5.2%
은 19
 
4.7%
행 19
 
4.7%
협 15
 
3.7%
신 12
 
3.0%
동 11
 
2.7%
인 10
 
2.5%
Other values (75) 202
50.4%
Latin
ValueCountFrequency (%)
B 2
33.3%
C 1
16.7%
P 1
16.7%
S 1
16.7%
K 1
16.7%
Common
ValueCountFrequency (%)
25
89.3%
2 1
 
3.6%
) 1
 
3.6%
( 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 401
92.2%
ASCII 34
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 33
 
8.2%
지 32
 
8.0%
도 27
 
6.7%
송 21
 
5.2%
은 19
 
4.7%
행 19
 
4.7%
협 15
 
3.7%
신 12
 
3.0%
동 11
 
2.7%
인 10
 
2.5%
Other values (75) 202
50.4%
ASCII
ValueCountFrequency (%)
25
73.5%
B 2
 
5.9%
2 1
 
2.9%
C 1
 
2.9%
) 1
 
2.9%
P 1
 
2.9%
( 1
 
2.9%
S 1
 
2.9%
K 1
 
2.9%

주소
Text

MISSING 

Distinct37
Distinct (%)90.2%
Missing1163
Missing (%)96.6%
Memory size9.5 KiB
2024-01-28T16:52:29.395965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length19.902439
Min length16

Characters and Unicode

Total characters816
Distinct characters67
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

Unique33 ?
Unique (%)80.5%

Sample

1st row인천광역시 연수구 학나래로6번길 48
2nd row인천광역시 연수구 학나래로118번길 9
3rd row인천광역시 연수구 신송로 122 2층
4th row인천광역시 연수구 원인재로 59
5th row인천광역시 연수구 컨벤시아대로 81 3층
ValueCountFrequency (%)
인천광역시 41
22.7%
연수구 41
22.7%
2층 10
 
5.5%
컨벤시아대로 5
 
2.8%
원인재로 5
 
2.8%
신송로 4
 
2.2%
해돋이로 3
 
1.7%
3층 3
 
1.7%
해돋이로120번길 2
 
1.1%
먼우금로 2
 
1.1%
Other values (57) 65
35.9%
2024-01-28T16:52:29.712830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
17.2%
인 46
 
5.6%
시 46
 
5.6%
광 41
 
5.0%
역 41
 
5.0%
연 41
 
5.0%
수 41
 
5.0%
구 41
 
5.0%
천 41
 
5.0%
로 41
 
5.0%
Other values (57) 297
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
65.8%
Space Separator 140
 
17.2%
Decimal Number 138
 
16.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 46
 
8.6%
시 46
 
8.6%
광 41
 
7.6%
역 41
 
7.6%
연 41
 
7.6%
수 41
 
7.6%
구 41
 
7.6%
천 41
 
7.6%
로 41
 
7.6%
층 13
 
2.4%
Other values (45) 145
27.0%
Decimal Number
ValueCountFrequency (%)
1 35
25.4%
2 32
23.2%
0 15
10.9%
4 12
 
8.7%
6 10
 
7.2%
3 10
 
7.2%
8 8
 
5.8%
9 6
 
4.3%
5 6
 
4.3%
7 4
 
2.9%
Space Separator
ValueCountFrequency (%)
140
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 537
65.8%
Common 279
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 46
 
8.6%
시 46
 
8.6%
광 41
 
7.6%
역 41
 
7.6%
연 41
 
7.6%
수 41
 
7.6%
구 41
 
7.6%
천 41
 
7.6%
로 41
 
7.6%
층 13
 
2.4%
Other values (45) 145
27.0%
Common
ValueCountFrequency (%)
140
50.2%
1 35
 
12.5%
2 32
 
11.5%
0 15
 
5.4%
4 12
 
4.3%
6 10
 
3.6%
3 10
 
3.6%
8 8
 
2.9%
9 6
 
2.2%
5 6
 
2.2%
Other values (2) 5
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
65.8%
ASCII 279
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
50.2%
1 35
 
12.5%
2 32
 
11.5%
0 15
 
5.4%
4 12
 
4.3%
6 10
 
3.6%
3 10
 
3.6%
8 8
 
2.9%
9 6
 
2.2%
5 6
 
2.2%
Other values (2) 5
 
1.8%
Hangul
ValueCountFrequency (%)
인 46
 
8.6%
시 46
 
8.6%
광 41
 
7.6%
역 41
 
7.6%
연 41
 
7.6%
수 41
 
7.6%
구 41
 
7.6%
천 41
 
7.6%
로 41
 
7.6%
층 13
 
2.4%
Other values (45) 145
27.0%

위도
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)85.4%
Missing1163
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean37.403498
Minimum37.379109
Maximum37.428673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.7 KiB
2024-01-28T16:52:29.822398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.379109
5-th percentile37.382084
Q137.393282
median37.39626
Q337.416657
95-th percentile37.425166
Maximum37.428673
Range0.049564
Interquartile range (IQR)0.023375

Descriptive statistics

Standard deviation0.014526835
Coefficient of variation (CV)0.00038838172
Kurtosis-1.0960395
Mean37.403498
Median Absolute Deviation (MAD)0.009135
Skewness0.24476902
Sum1533.5434
Variance0.00021102893
MonotonicityNot monotonic
2024-01-28T16:52:29.925235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
37.382084 2
 
0.2%
37.395661 2
 
0.2%
37.395261 2
 
0.2%
37.379109 2
 
0.2%
37.395714 2
 
0.2%
37.405395 2
 
0.2%
37.394901 1
 
0.1%
37.428673 1
 
0.1%
37.420713 1
 
0.1%
37.415288 1
 
0.1%
Other values (25) 25
 
2.1%
(Missing) 1163
96.6%
ValueCountFrequency (%)
37.379109 2
0.2%
37.382084 2
0.2%
37.39014 1
0.1%
37.391371 1
0.1%
37.391602 1
0.1%
37.391814 1
0.1%
37.392452 1
0.1%
37.393256 1
0.1%
37.393282 1
0.1%
37.39333 1
0.1%
ValueCountFrequency (%)
37.428673 1
0.1%
37.427925 1
0.1%
37.425166 1
0.1%
37.424584 1
0.1%
37.424486 1
0.1%
37.424479 1
0.1%
37.423928 1
0.1%
37.420713 1
0.1%
37.417396 1
0.1%
37.417053 1
0.1%

경도
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)85.4%
Missing1163
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean126.66248
Minimum126.64491
Maximum126.70132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.7 KiB
2024-01-28T16:52:30.032691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.64491
5-th percentile126.64624
Q1126.65068
median126.65244
Q3126.67275
95-th percentile126.69813
Maximum126.70132
Range0.056409
Interquartile range (IQR)0.02206

Descriptive statistics

Standard deviation0.016419069
Coefficient of variation (CV)0.00012962852
Kurtosis-0.079060815
Mean126.66248
Median Absolute Deviation (MAD)0.005034
Skewness1.0365524
Sum5193.1615
Variance0.00026958584
MonotonicityNot monotonic
2024-01-28T16:52:30.130840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
126.654663 2
 
0.2%
126.650954 2
 
0.2%
126.651875 2
 
0.2%
126.650591 2
 
0.2%
126.652444 2
 
0.2%
126.672745 2
 
0.2%
126.650156 1
 
0.1%
126.663269 1
 
0.1%
126.694656 1
 
0.1%
126.676346 1
 
0.1%
Other values (25) 25
 
2.1%
(Missing) 1163
96.6%
ValueCountFrequency (%)
126.644908 1
0.1%
126.645626 1
0.1%
126.646239 1
0.1%
126.647226 1
0.1%
126.649717 1
0.1%
126.649982 1
0.1%
126.650156 1
0.1%
126.650301 1
0.1%
126.650591 2
0.2%
126.650685 1
0.1%
ValueCountFrequency (%)
126.701317 1
0.1%
126.698447 1
0.1%
126.698128 1
0.1%
126.694656 1
0.1%
126.684756 1
0.1%
126.684475 1
0.1%
126.676677 1
0.1%
126.676346 1
0.1%
126.676195 1
0.1%
126.675401 1
0.1%

전화번호
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing1163
Missing (%)96.6%
Memory size9.5 KiB
2024-01-28T16:52:30.317594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters492
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

Unique41 ?
Unique (%)100.0%

Sample

1st row032-822-9101
2nd row032-814-6414
3rd row032-851-0371
4th row032-815-2472
5th row032-858-2460
ValueCountFrequency (%)
032-833-2605 1
 
2.4%
032-831-2029 1
 
2.4%
032-831-2050 1
 
2.4%
032-831-5641 1
 
2.4%
032-851-2164 1
 
2.4%
032-851-0520 1
 
2.4%
032-831-6321 1
 
2.4%
032-220-2114 1
 
2.4%
032-816-3511 1
 
2.4%
032-821-0320 1
 
2.4%
Other values (31) 31
75.6%
2024-01-28T16:52:30.616576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 82
16.7%
0 80
16.3%
2 78
15.9%
3 69
14.0%
8 54
11.0%
1 47
9.6%
5 27
 
5.5%
4 18
 
3.7%
6 15
 
3.0%
7 14
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 410
83.3%
Dash Punctuation 82
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80
19.5%
2 78
19.0%
3 69
16.8%
8 54
13.2%
1 47
11.5%
5 27
 
6.6%
4 18
 
4.4%
6 15
 
3.7%
7 14
 
3.4%
9 8
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 492
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 82
16.7%
0 80
16.3%
2 78
15.9%
3 69
14.0%
8 54
11.0%
1 47
9.6%
5 27
 
5.5%
4 18
 
3.7%
6 15
 
3.0%
7 14
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 492
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 82
16.7%
0 80
16.3%
2 78
15.9%
3 69
14.0%
8 54
11.0%
1 47
9.6%
5 27
 
5.5%
4 18
 
3.7%
6 15
 
3.0%
7 14
 
2.8%

Interactions

2024-01-28T16:52:28.360230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:52:28.183423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:52:28.430560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:52:28.276191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T16:52:30.970075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
금융기관명주소위도경도전화번호
금융기관명1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
위도1.0001.0001.0000.9411.000
경도1.0001.0000.9411.0001.000
전화번호1.0001.0001.0001.0001.000
2024-01-28T16:52:31.056567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.433
경도0.4331.000

Missing values

2024-01-28T16:52:28.524929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T16:52:28.608800image/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.
2024-01-28T16:52:28.694903image/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

금융기관명주소위도경도전화번호
0경인북부수협 선학지점인천광역시 연수구 학나래로6번길 4837.425166126.698128032-822-9101
1관교문학새마을금고 제2분소인천광역시 연수구 학나래로118번길 937.427925126.698447032-814-6414
2국민은행 송도지점인천광역시 연수구 신송로 122 2층37.395714126.652444032-851-0371
3국민은행동춘동지점인천광역시 연수구 원인재로 5937.405395126.672745032-815-2472
4국민은행송도PB센터인천광역시 연수구 컨벤시아대로 81 3층37.394901126.650156032-858-2460
5기업은행 송도테크노파크지점인천광역시 연수구 갯벌로 1237.382084126.654663032-260-1236
6남인천농협 선학지점인천광역시 연수구 선학로 7237.423928126.701317032-820-5700
7남인천농협 송도신도시지점인천광역시 연수구 신송로82번길 6 101호37.393282126.657478032-830-5300
8남인천농협동막지점인천광역시 연수구 원인재로 1437.401583126.671079032-812-7056
9남인천농협소암영농회인천광역시 연수구 능허대로 35337.416201126.649982032-833-2605
금융기관명주소위도경도전화번호
1194<NA><NA><NA><NA><NA>
1195<NA><NA><NA><NA><NA>
1196<NA><NA><NA><NA><NA>
1197<NA><NA><NA><NA><NA>
1198<NA><NA><NA><NA><NA>
1199<NA><NA><NA><NA><NA>
1200<NA><NA><NA><NA><NA>
1201<NA><NA><NA><NA><NA>
1202<NA><NA><NA><NA><NA>
1203<NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

금융기관명주소위도경도전화번호# duplicates
0<NA><NA><NA><NA><NA>1163