Overview

Dataset statistics

Number of variables6
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory55.9 B

Variable types

Numeric3
Text2
Categorical1

Dataset

Description서울특별시 송파구 동주민센터 현황에 대한 데이터입니다. 서울특별시 송파구 동주민센터의 위 경도 데이터 및 소재지 데이터를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15116616/fileData.do

Alerts

기준일자 has constant value ""Constant
연번 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
주민센터명 has unique valuesUnique
소재지 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:19:24.471281
Analysis finished2023-12-12 01:19:26.106773
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T10:19:26.174842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2023-12-12T10:19:26.331045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

주민센터명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T10:19:26.614452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.7777778
Min length3

Characters and Unicode

Total characters102
Distinct characters35
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

Unique27 ?
Unique (%)100.0%

Sample

1st row가락1동
2nd row가락2동
3rd row가락본동
4th row거여1동
5th row거여2동
ValueCountFrequency (%)
가락1동 1
 
3.7%
송파2동 1
 
3.7%
풍납1동 1
 
3.7%
장지동 1
 
3.7%
잠실본동 1
 
3.7%
잠실7동 1
 
3.7%
잠실6동 1
 
3.7%
잠실4동 1
 
3.7%
잠실3동 1
 
3.7%
잠실2동 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T10:19:27.025044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 27
26.5%
2 8
 
7.8%
1 7
 
6.9%
실 6
 
5.9%
잠 6
 
5.9%
가 3
 
2.9%
락 3
 
2.9%
이 2
 
2.0%
풍 2
 
2.0%
오 2
 
2.0%
Other values (25) 36
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83
81.4%
Decimal Number 19
 
18.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 27
32.5%
실 6
 
7.2%
잠 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
이 2
 
2.4%
풍 2
 
2.4%
오 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
Decimal Number
ValueCountFrequency (%)
2 8
42.1%
1 7
36.8%
3 1
 
5.3%
7 1
 
5.3%
6 1
 
5.3%
4 1
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83
81.4%
Common 19
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 27
32.5%
실 6
 
7.2%
잠 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
이 2
 
2.4%
풍 2
 
2.4%
오 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
Common
ValueCountFrequency (%)
2 8
42.1%
1 7
36.8%
3 1
 
5.3%
7 1
 
5.3%
6 1
 
5.3%
4 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83
81.4%
ASCII 19
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 27
32.5%
실 6
 
7.2%
잠 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
이 2
 
2.4%
풍 2
 
2.4%
오 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
ASCII
ValueCountFrequency (%)
2 8
42.1%
1 7
36.8%
3 1
 
5.3%
7 1
 
5.3%
6 1
 
5.3%
4 1
 
5.3%

소재지
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T10:19:27.320611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length27
Mean length24.37037
Min length18

Characters and Unicode

Total characters658
Distinct characters71
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row서울특별시 송파구 양재대로 925 (가락동 479)
2nd row서울특별시 송파구 중대로 20길 6(가락동)
3rd row서울특별시 송파구 송파대로 28길 39(가락동)
4th row서울특별시 송파구 오금로 53길 32(거여동)
5th row서울특별시 송파구 거마로2길 19(거여동)
ValueCountFrequency (%)
서울특별시 27
22.3%
송파구 27
22.3%
백제고분로 4
 
3.3%
중대로 3
 
2.5%
양재대로 2
 
1.7%
올림픽로 2
 
1.7%
마천로 2
 
1.7%
5(오금동 1
 
0.8%
1232(방이동 1
 
0.8%
위례광장로 1
 
0.8%
Other values (51) 51
42.1%
2023-12-12T10:19:27.796108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
 
14.3%
송 31
 
4.7%
파 30
 
4.6%
시 28
 
4.3%
서 27
 
4.1%
특 27
 
4.1%
별 27
 
4.1%
구 27
 
4.1%
울 27
 
4.1%
로 27
 
4.1%
Other values (61) 313
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 416
63.2%
Decimal Number 95
 
14.4%
Space Separator 94
 
14.3%
Close Punctuation 25
 
3.8%
Open Punctuation 25
 
3.8%
Other Punctuation 2
 
0.3%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 31
 
7.5%
파 30
 
7.2%
시 28
 
6.7%
서 27
 
6.5%
특 27
 
6.5%
별 27
 
6.5%
구 27
 
6.5%
울 27
 
6.5%
로 27
 
6.5%
동 26
 
6.2%
Other values (46) 139
33.4%
Decimal Number
ValueCountFrequency (%)
2 19
20.0%
1 17
17.9%
3 13
13.7%
5 11
11.6%
9 9
9.5%
6 9
9.5%
7 5
 
5.3%
8 4
 
4.2%
0 4
 
4.2%
4 4
 
4.2%
Space Separator
ValueCountFrequency (%)
94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Other Punctuation
ValueCountFrequency (%)
， 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 416
63.2%
Common 242
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 31
 
7.5%
파 30
 
7.2%
시 28
 
6.7%
서 27
 
6.5%
특 27
 
6.5%
별 27
 
6.5%
구 27
 
6.5%
울 27
 
6.5%
로 27
 
6.5%
동 26
 
6.2%
Other values (46) 139
33.4%
Common
ValueCountFrequency (%)
94
38.8%
) 25
 
10.3%
( 25
 
10.3%
2 19
 
7.9%
1 17
 
7.0%
3 13
 
5.4%
5 11
 
4.5%
9 9
 
3.7%
6 9
 
3.7%
7 5
 
2.1%
Other values (5) 15
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 416
63.2%
ASCII 240
36.5%
None 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
39.2%
) 25
 
10.4%
( 25
 
10.4%
2 19
 
7.9%
1 17
 
7.1%
3 13
 
5.4%
5 11
 
4.6%
9 9
 
3.8%
6 9
 
3.8%
7 5
 
2.1%
Other values (4) 13
 
5.4%
Hangul
ValueCountFrequency (%)
송 31
 
7.5%
파 30
 
7.2%
시 28
 
6.7%
서 27
 
6.5%
특 27
 
6.5%
별 27
 
6.5%
구 27
 
6.5%
울 27
 
6.5%
로 27
 
6.5%
동 26
 
6.2%
Other values (46) 139
33.4%
None
ValueCountFrequency (%)
， 2
100.0%

위도
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.11767
Minimum127.07666
Maximum127.14995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T10:19:27.984417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.07666
5-th percentile127.0856
Q1127.1065
median127.11678
Q3127.13027
95-th percentile127.14802
Maximum127.14995
Range0.0732948
Interquartile range (IQR)0.02376505

Descriptive statistics

Standard deviation0.020106982
Coefficient of variation (CV)0.00015817614
Kurtosis-0.59881527
Mean127.11767
Median Absolute Deviation (MAD)0.0130943
Skewness-0.18036262
Sum3432.1771
Variance0.00040429073
MonotonicityNot monotonic
2023-12-12T10:19:28.165973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
127.1098575 1
 
3.7%
127.1266485 1
 
3.7%
127.1167831 1
 
3.7%
127.1220705 1
 
3.7%
127.1324284 1
 
3.7%
127.0843509 1
 
3.7%
127.076659 1
 
3.7%
127.100664 1
 
3.7%
127.112235 1
 
3.7%
127.0943873 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
127.076659 1
3.7%
127.0843509 1
3.7%
127.0885232 1
3.7%
127.092525 1
3.7%
127.0943873 1
3.7%
127.100664 1
3.7%
127.1036888 1
3.7%
127.1093121 1
3.7%
127.1098575 1
3.7%
127.1109197 1
3.7%
ValueCountFrequency (%)
127.1499538 1
3.7%
127.1485419 1
3.7%
127.1468043 1
3.7%
127.1439371 1
3.7%
127.1433273 1
3.7%
127.1342813 1
3.7%
127.1324284 1
3.7%
127.1281026 1
3.7%
127.1266485 1
3.7%
127.1241714 1
3.7%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.504642
Minimum37.481167
Maximum37.538089
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T10:19:28.363002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.481167
5-th percentile37.487802
Q137.496255
median37.503001
Q337.512574
95-th percentile37.526181
Maximum37.538089
Range0.0569213
Interquartile range (IQR)0.01631865

Descriptive statistics

Standard deviation0.012909004
Coefficient of variation (CV)0.00034419751
Kurtosis0.54703633
Mean37.504642
Median Absolute Deviation (MAD)0.0079162
Skewness0.61536848
Sum1012.6253
Variance0.00016664239
MonotonicityNot monotonic
2023-12-12T10:19:28.824054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
37.4965037 1
 
3.7%
37.4987015 1
 
3.7%
37.5287594 1
 
3.7%
37.5380886 1
 
3.7%
37.4869042 1
 
3.7%
37.5061483 1
 
3.7%
37.5080527 1
 
3.7%
37.5181224 1
 
3.7%
37.5201653 1
 
3.7%
37.5133079 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
37.4811673 1
3.7%
37.4869042 1
3.7%
37.489898 1
3.7%
37.490015 1
3.7%
37.4935145 1
3.7%
37.4955929 1
3.7%
37.4960061 1
3.7%
37.4965037 1
3.7%
37.4968519 1
3.7%
37.4969494 1
3.7%
ValueCountFrequency (%)
37.5380886 1
3.7%
37.5287594 1
3.7%
37.5201653 1
3.7%
37.5181224 1
3.7%
37.5154452 1
3.7%
37.5145684 1
3.7%
37.5133079 1
3.7%
37.5118392 1
3.7%
37.5109174 1
3.7%
37.5080527 1
3.7%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-06-30
27 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-30
2nd row2023-06-30
3rd row2023-06-30
4th row2023-06-30
5th row2023-06-30

Common Values

ValueCountFrequency (%)
2023-06-30 27
100.0%

Length

2023-12-12T10:19:28.976779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:19:29.073880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-30 27
100.0%

Interactions

2023-12-12T10:19:25.473600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:24.692918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:25.030546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:25.610213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:24.806881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:25.154766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:25.744020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:24.918041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:19:25.311401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:19:29.133897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주민센터명소재지위도경도
연번1.0001.0001.0000.4200.660
주민센터명1.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.000
위도0.4201.0001.0001.0000.000
경도0.6601.0001.0000.0001.000
2023-12-12T10:19:29.223323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.3790.564
위도-0.3791.000-0.441
경도0.564-0.4411.000

Missing values

2023-12-12T10:19:25.908624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:19:26.063425image/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

연번주민센터명소재지위도경도기준일자
01가락1동서울특별시 송파구 양재대로 925 (가락동 479)127.10985837.4965042023-06-30
12가락2동서울특별시 송파구 중대로 20길 6(가락동)127.12664937.4987022023-06-30
23가락본동서울특별시 송파구 송파대로 28길 39(가락동)127.12179937.4955932023-06-30
34거여1동서울특별시 송파구 오금로 53길 32(거여동)127.14332737.4969492023-06-30
45거여2동서울특별시 송파구 거마로2길 19(거여동)127.14680437.4935152023-06-30
56마천1동서울특별시 송파구 마천로 303(마천동)127.14995437.4960062023-06-30
67마천2동서울특별시 송파구 마천로 287(마천동)127.14854237.4968522023-06-30
78문정1동서울특별시 송파구 동남로 116(문정동)127.12417137.4900152023-06-30
89문정2동서울특별시 송파구 중대로 16(문정동)127.1109237.4898982023-06-30
910방이1동서울특별시 송파구 위례성대로 16길 22(방이동)127.12389337.5109172023-06-30
연번주민센터명소재지위도경도기준일자
1718위례동서울특별시 송파구 위례광장로 210(장지동 882)127.14393737.4811672023-06-30
1819잠실2동서울특별시 송파구 올림픽로 159(잠실동)127.08852337.5118392023-06-30
1920잠실3동서울특별시 송파구 잠실로 51-31(잠실동)127.09438737.5133082023-06-30
2021잠실4동서울특별시 송파구 올림픽로 35길 16(신천동)127.11223537.5201652023-06-30
2122잠실6동서울특별시 송파구 올림픽로35길 120(신천동)127.10066437.5181222023-06-30
2223잠실7동서울특별시 송파구 올림픽로4길 17，상가2층 (잠실동，아시아선수촌)127.07665937.5080532023-06-30
2324잠실본동서울특별시 송파구 백제고분로 15길 9(잠실동)127.08435137.5061482023-06-30
2425장지동서울특별시 송파구 새말로 19길 6(문정동)127.13242837.4869042023-06-30
2526풍납1동서울특별시 송파구 천호대로 152길 7(풍납동)127.12207137.5380892023-06-30
2627풍납2동서울특별시 송파구 토성로 64(풍납동)127.11678337.5287592023-06-30