Overview

Dataset statistics

Number of variables13
Number of observations3606
Missing cells7235
Missing cells (%)15.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory380.4 KiB
Average record size in memory108.0 B

Variable types

Numeric3
Unsupported1
Text6
Categorical2
DateTime1

Dataset

Description아이디,새주소 아이디,시설 아이디,시설명,위도,경도,건물군여부,시설용도분류,소재지 도로명주소,소재지 지번주소,기타,국가지점번호,데이터 기준일자
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21698/S/1/datasetView.do

Alerts

데이터 기준일자 has constant value ""Constant
아이디 is highly overall correlated with 시설용도분류High correlation
시설용도분류 is highly overall correlated with 아이디High correlation
새주소 아이디 has 3606 (100.0%) missing valuesMissing
소재지 도로명주소 has 112 (3.1%) missing valuesMissing
기타 has 3517 (97.5%) missing valuesMissing
아이디 has unique valuesUnique
시설 아이디 has unique valuesUnique
새주소 아이디 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 07:32:22.071089
Analysis finished2023-12-11 07:32:26.511637
Duration4.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3606
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1803.5
Minimum1
Maximum3606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2023-12-11T16:32:26.634418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile181.25
Q1902.25
median1803.5
Q32704.75
95-th percentile3425.75
Maximum3606
Range3605
Interquartile range (IQR)1802.5

Descriptive statistics

Standard deviation1041.1069
Coefficient of variation (CV)0.57727023
Kurtosis-1.2
Mean1803.5
Median Absolute Deviation (MAD)901.5
Skewness0
Sum6503421
Variance1083903.5
MonotonicityNot monotonic
2023-12-11T16:32:26.868668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3007 1
 
< 0.1%
918 1
 
< 0.1%
1058 1
 
< 0.1%
1059 1
 
< 0.1%
1060 1
 
< 0.1%
1064 1
 
< 0.1%
1069 1
 
< 0.1%
1070 1
 
< 0.1%
1071 1
 
< 0.1%
1072 1
 
< 0.1%
Other values (3596) 3596
99.7%
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 (%)
3606 1
< 0.1%
3605 1
< 0.1%
3604 1
< 0.1%
3603 1
< 0.1%
3602 1
< 0.1%
3601 1
< 0.1%
3600 1
< 0.1%
3599 1
< 0.1%
3598 1
< 0.1%
3597 1
< 0.1%

새주소 아이디
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3606
Missing (%)100.0%
Memory size31.8 KiB

시설 아이디
Text

UNIQUE 

Distinct3606
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2023-12-11T16:32:27.379371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters18030
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3606 ?
Unique (%)100.0%

Sample

1st rowP0877
2nd rowP0878
3rd rowP0879
4th rowP0880
5th rowP0882
ValueCountFrequency (%)
p0877 1
 
< 0.1%
b0916 1
 
< 0.1%
b1056 1
 
< 0.1%
b1075 1
 
< 0.1%
b1057 1
 
< 0.1%
b1058 1
 
< 0.1%
b1059 1
 
< 0.1%
b1060 1
 
< 0.1%
b1064 1
 
< 0.1%
b1069 1
 
< 0.1%
Other values (3596) 3596
99.7%
2023-12-11T16:32:28.097878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3277
18.2%
1 2618
14.5%
B 2146
11.9%
P 1452
8.1%
2 1263
 
7.0%
3 1126
 
6.2%
4 1083
 
6.0%
5 1021
 
5.7%
7 1010
 
5.6%
6 1010
 
5.6%
Other values (3) 2024
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14424
80.0%
Uppercase Letter 3606
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3277
22.7%
1 2618
18.2%
2 1263
 
8.8%
3 1126
 
7.8%
4 1083
 
7.5%
5 1021
 
7.1%
7 1010
 
7.0%
6 1010
 
7.0%
8 1009
 
7.0%
9 1007
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
B 2146
59.5%
P 1452
40.3%
R 8
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 14424
80.0%
Latin 3606
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3277
22.7%
1 2618
18.2%
2 1263
 
8.8%
3 1126
 
7.8%
4 1083
 
7.5%
5 1021
 
7.1%
7 1010
 
7.0%
6 1010
 
7.0%
8 1009
 
7.0%
9 1007
 
7.0%
Latin
ValueCountFrequency (%)
B 2146
59.5%
P 1452
40.3%
R 8
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3277
18.2%
1 2618
14.5%
B 2146
11.9%
P 1452
8.1%
2 1263
 
7.0%
3 1126
 
6.2%
4 1083
 
6.0%
5 1021
 
5.7%
7 1010
 
5.6%
6 1010
 
5.6%
Other values (3) 2024
11.2%

시설명
Text

Distinct3370
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2023-12-11T16:32:28.603761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length6.5865225
Min length2

Characters and Unicode

Total characters23751
Distinct characters681
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3214 ?
Unique (%)89.1%

Sample

1st row꿈동산어린이공원
2nd row미화어린이공원
3rd row꿈동산어린이공원
4th row새움어린이공원
5th row동산어린이공원
ValueCountFrequency (%)
보건소 23
 
0.6%
의료법인 16
 
0.4%
박물관 16
 
0.4%
홈플러스 13
 
0.3%
이마트 12
 
0.3%
개나리공원 10
 
0.3%
보건지소 9
 
0.2%
근린공원 9
 
0.2%
새싹공원 8
 
0.2%
무궁화공원 8
 
0.2%
Other values (3501) 3785
96.8%
2023-12-11T16:32:29.325251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 2317
 
9.8%
공 1445
 
6.1%
이 602
 
2.5%
린 561
 
2.4%
병 524
 
2.2%
서 457
 
1.9%
어 403
 
1.7%
관 389
 
1.6%
의 375
 
1.6%
305
 
1.3%
Other values (671) 16373
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22911
96.5%
Space Separator 305
 
1.3%
Decimal Number 163
 
0.7%
Uppercase Letter 157
 
0.7%
Open Punctuation 65
 
0.3%
Close Punctuation 64
 
0.3%
Lowercase Letter 41
 
0.2%
Other Symbol 21
 
0.1%
Dash Punctuation 10
 
< 0.1%
Other Punctuation 6
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 2317
 
10.1%
공 1445
 
6.3%
이 602
 
2.6%
린 561
 
2.4%
병 524
 
2.3%
서 457
 
2.0%
어 403
 
1.8%
관 389
 
1.7%
의 375
 
1.6%
빌 304
 
1.3%
Other values (602) 15534
67.8%
Uppercase Letter
ValueCountFrequency (%)
S 17
 
10.8%
C 15
 
9.6%
E 11
 
7.0%
A 10
 
6.4%
W 10
 
6.4%
K 9
 
5.7%
T 9
 
5.7%
I 9
 
5.7%
O 9
 
5.7%
R 8
 
5.1%
Other values (14) 50
31.8%
Lowercase Letter
ValueCountFrequency (%)
e 9
22.0%
c 4
9.8%
l 4
9.8%
t 3
 
7.3%
i 3
 
7.3%
m 2
 
4.9%
o 2
 
4.9%
u 2
 
4.9%
s 2
 
4.9%
n 2
 
4.9%
Other values (8) 8
19.5%
Decimal Number
ValueCountFrequency (%)
1 40
24.5%
2 36
22.1%
3 16
 
9.8%
0 15
 
9.2%
5 15
 
9.2%
6 10
 
6.1%
8 10
 
6.1%
4 9
 
5.5%
9 7
 
4.3%
7 5
 
3.1%
Other Punctuation
ValueCountFrequency (%)
? 2
33.3%
& 1
16.7%
, 1
16.7%
' 1
16.7%
. 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 64
98.5%
[ 1
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 63
98.4%
] 1
 
1.6%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
305
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22932
96.6%
Common 618
 
2.6%
Latin 201
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 2317
 
10.1%
공 1445
 
6.3%
이 602
 
2.6%
린 561
 
2.4%
병 524
 
2.3%
서 457
 
2.0%
어 403
 
1.8%
관 389
 
1.7%
의 375
 
1.6%
빌 304
 
1.3%
Other values (603) 15555
67.8%
Latin
ValueCountFrequency (%)
S 17
 
8.5%
C 15
 
7.5%
E 11
 
5.5%
A 10
 
5.0%
W 10
 
5.0%
K 9
 
4.5%
T 9
 
4.5%
I 9
 
4.5%
e 9
 
4.5%
O 9
 
4.5%
Other values (34) 93
46.3%
Common
ValueCountFrequency (%)
305
49.4%
( 64
 
10.4%
) 63
 
10.2%
1 40
 
6.5%
2 36
 
5.8%
3 16
 
2.6%
0 15
 
2.4%
5 15
 
2.4%
6 10
 
1.6%
- 10
 
1.6%
Other values (14) 44
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22911
96.5%
ASCII 816
 
3.4%
None 21
 
0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 2317
 
10.1%
공 1445
 
6.3%
이 602
 
2.6%
린 561
 
2.4%
병 524
 
2.3%
서 457
 
2.0%
어 403
 
1.8%
관 389
 
1.7%
의 375
 
1.6%
빌 304
 
1.3%
Other values (602) 15534
67.8%
ASCII
ValueCountFrequency (%)
305
37.4%
( 64
 
7.8%
) 63
 
7.7%
1 40
 
4.9%
2 36
 
4.4%
S 17
 
2.1%
3 16
 
2.0%
0 15
 
1.8%
C 15
 
1.8%
5 15
 
1.8%
Other values (56) 230
28.2%
None
ValueCountFrequency (%)
㈜ 21
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%

위도
Real number (ℝ)

Distinct3458
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.54261
Minimum37.43486
Maximum37.68895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2023-12-11T16:32:29.558492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.43486
5-th percentile37.468743
Q137.499394
median37.538082
Q337.574043
95-th percentile37.64644
Maximum37.68895
Range0.25409
Interquartile range (IQR)0.07464925

Descriptive statistics

Standard deviation0.053232011
Coefficient of variation (CV)0.0014179092
Kurtosis-0.47902474
Mean37.54261
Median Absolute Deviation (MAD)0.0376085
Skewness0.48921074
Sum135378.65
Variance0.002833647
MonotonicityNot monotonic
2023-12-11T16:32:29.788447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.574482 3
 
0.1%
37.51626 3
 
0.1%
37.502254 3
 
0.1%
37.521713 3
 
0.1%
37.497932 3
 
0.1%
37.456833 3
 
0.1%
37.505466 3
 
0.1%
37.569466 2
 
0.1%
37.49126 2
 
0.1%
37.542202 2
 
0.1%
Other values (3448) 3579
99.3%
ValueCountFrequency (%)
37.43486 1
< 0.1%
37.43558 1
< 0.1%
37.438725 1
< 0.1%
37.439613 1
< 0.1%
37.44152 1
< 0.1%
37.44317 1
< 0.1%
37.44665 1
< 0.1%
37.447502 1
< 0.1%
37.447655 1
< 0.1%
37.447937 1
< 0.1%
ValueCountFrequency (%)
37.68895 1
< 0.1%
37.685654 1
< 0.1%
37.68433 1
< 0.1%
37.683834 1
< 0.1%
37.682625 1
< 0.1%
37.682224 1
< 0.1%
37.680798 1
< 0.1%
37.68073 1
< 0.1%
37.680634 1
< 0.1%
37.68063 1
< 0.1%

경도
Real number (ℝ)

Distinct3414
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99014
Minimum126.79639
Maximum127.18037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.8 KiB
2023-12-11T16:32:30.006878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.79639
5-th percentile126.83917
Q1126.91016
median127.00881
Q3127.06115
95-th percentile127.13332
Maximum127.18037
Range0.38398
Interquartile range (IQR)0.1509925

Descriptive statistics

Standard deviation0.091121334
Coefficient of variation (CV)0.00071754651
Kurtosis-1.0245845
Mean126.99014
Median Absolute Deviation (MAD)0.074338
Skewness-0.12429235
Sum457926.46
Variance0.0083030975
MonotonicityNot monotonic
2023-12-11T16:32:30.240247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.836006 5
 
0.1%
127.06191 4
 
0.1%
127.06417 4
 
0.1%
126.90479 3
 
0.1%
127.05102 3
 
0.1%
127.06518 3
 
0.1%
126.89541 3
 
0.1%
126.95604 3
 
0.1%
127.02443 3
 
0.1%
127.07109 3
 
0.1%
Other values (3404) 3572
99.1%
ValueCountFrequency (%)
126.79639 1
< 0.1%
126.79888 1
< 0.1%
126.80141 1
< 0.1%
126.803085 1
< 0.1%
126.80323 1
< 0.1%
126.8065 1
< 0.1%
126.80675 1
< 0.1%
126.80703 1
< 0.1%
126.80767 1
< 0.1%
126.80784 1
< 0.1%
ValueCountFrequency (%)
127.18037 1
< 0.1%
127.17785 1
< 0.1%
127.17666 1
< 0.1%
127.17566 1
< 0.1%
127.17458 1
< 0.1%
127.174576 1
< 0.1%
127.174545 1
< 0.1%
127.17451 1
< 0.1%
127.17418 1
< 0.1%
127.174095 1
< 0.1%

건물군여부
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
BG_AA
1566 
<NA>
1346 
BG_AB
676 
FU_BA
 
18

Length

Max length5
Median length5
Mean length4.6267332
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BG_AA 1566
43.4%
<NA> 1346
37.3%
BG_AB 676
18.7%
FU_BA 18
 
0.5%

Length

2023-12-11T16:32:30.428866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:32:30.589933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bg_aa 1566
43.4%
na 1346
37.3%
bg_ab 676
18.7%
fu_ba 18
 
0.5%

시설용도분류
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
FU_BI
1452 
FU_BA
893 
FU_BD
525 
FU_BE
271 
FU_BB
205 
Other values (5)
260 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
FU_BI 1452
40.3%
FU_BA 893
24.8%
FU_BD 525
 
14.6%
FU_BE 271
 
7.5%
FU_BB 205
 
5.7%
FU_BC 169
 
4.7%
FU_BH 31
 
0.9%
FU_BG 26
 
0.7%
FU_BF 26
 
0.7%
FU_BJ 8
 
0.2%

Length

2023-12-11T16:32:30.770113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:32:30.931653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
fu_bi 1452
40.3%
fu_ba 893
24.8%
fu_bd 525
 
14.6%
fu_be 271
 
7.5%
fu_bb 205
 
5.7%
fu_bc 169
 
4.7%
fu_bh 31
 
0.9%
fu_bg 26
 
0.7%
fu_bf 26
 
0.7%
fu_bj 8
 
0.2%

소재지 도로명주소
Text

MISSING 

Distinct3370
Distinct (%)96.5%
Missing112
Missing (%)3.1%
Memory size28.3 KiB
2023-12-11T16:32:31.444053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.543503
Min length14

Characters and Unicode

Total characters64791
Distinct characters285
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

Unique3261 ?
Unique (%)93.3%

Sample

1st row서울특별시 도봉구 도봉로110나길 99
2nd row서울특별시 도봉구 도봉로 564
3rd row서울특별시 동대문구 황물로 42
4th row서울특별시 동대문구 천호대로55길 11
5th row서울특별시 동대문구 전농로2나길 7
ValueCountFrequency (%)
서울특별시 3494
25.0%
강남구 334
 
2.4%
강서구 257
 
1.8%
송파구 251
 
1.8%
서초구 201
 
1.4%
금천구 196
 
1.4%
노원구 190
 
1.4%
강동구 163
 
1.2%
양천구 144
 
1.0%
영등포구 142
 
1.0%
Other values (2839) 8604
61.6%
2023-12-11T16:32:32.155444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10482
16.2%
서 4213
 
6.5%
구 3671
 
5.7%
로 3624
 
5.6%
시 3587
 
5.5%
울 3504
 
5.4%
별 3494
 
5.4%
특 3494
 
5.4%
1 2339
 
3.6%
2 1658
 
2.6%
Other values (275) 24725
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42045
64.9%
Decimal Number 11814
 
18.2%
Space Separator 10482
 
16.2%
Dash Punctuation 450
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 4213
 
10.0%
구 3671
 
8.7%
로 3624
 
8.6%
시 3587
 
8.5%
울 3504
 
8.3%
별 3494
 
8.3%
특 3494
 
8.3%
길 1568
 
3.7%
강 986
 
2.3%
동 750
 
1.8%
Other values (263) 13154
31.3%
Decimal Number
ValueCountFrequency (%)
1 2339
19.8%
2 1658
14.0%
3 1403
11.9%
4 1142
9.7%
5 1070
9.1%
6 986
8.3%
0 878
 
7.4%
7 860
 
7.3%
8 747
 
6.3%
9 731
 
6.2%
Space Separator
ValueCountFrequency (%)
10482
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 450
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42045
64.9%
Common 22746
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 4213
 
10.0%
구 3671
 
8.7%
로 3624
 
8.6%
시 3587
 
8.5%
울 3504
 
8.3%
별 3494
 
8.3%
특 3494
 
8.3%
길 1568
 
3.7%
강 986
 
2.3%
동 750
 
1.8%
Other values (263) 13154
31.3%
Common
ValueCountFrequency (%)
10482
46.1%
1 2339
 
10.3%
2 1658
 
7.3%
3 1403
 
6.2%
4 1142
 
5.0%
5 1070
 
4.7%
6 986
 
4.3%
0 878
 
3.9%
7 860
 
3.8%
8 747
 
3.3%
Other values (2) 1181
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42045
64.9%
ASCII 22746
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10482
46.1%
1 2339
 
10.3%
2 1658
 
7.3%
3 1403
 
6.2%
4 1142
 
5.0%
5 1070
 
4.7%
6 986
 
4.3%
0 878
 
3.9%
7 860
 
3.8%
8 747
 
3.3%
Other values (2) 1181
 
5.2%
Hangul
ValueCountFrequency (%)
서 4213
 
10.0%
구 3671
 
8.7%
로 3624
 
8.6%
시 3587
 
8.5%
울 3504
 
8.3%
별 3494
 
8.3%
특 3494
 
8.3%
길 1568
 
3.7%
강 986
 
2.3%
동 750
 
1.8%
Other values (263) 13154
31.3%

소재지 지번주소
Text

Distinct3510
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2023-12-11T16:32:32.606541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length18.907654
Min length14

Characters and Unicode

Total characters68181
Distinct characters205
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

Unique3424 ?
Unique (%)95.0%

Sample

1st row서울특별시 도봉구 창동 663-1
2nd row서울특별시 도봉구 창동 715-17
3rd row서울특별시 동대문구 답십리동 1002-1
4th row서울특별시 동대문구 답십리동 1009-1
5th row서울특별시 동대문구 답십리동 998-1
ValueCountFrequency (%)
서울특별시 3606
24.9%
강남구 350
 
2.4%
강서구 267
 
1.8%
송파구 261
 
1.8%
서초구 210
 
1.4%
금천구 197
 
1.4%
노원구 196
 
1.4%
강동구 169
 
1.2%
영등포구 147
 
1.0%
양천구 145
 
1.0%
Other values (3383) 8949
61.7%
2023-12-11T16:32:33.245522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10891
16.0%
서 4273
 
6.3%
동 4001
 
5.9%
구 3816
 
5.6%
시 3688
 
5.4%
특 3606
 
5.3%
별 3606
 
5.3%
울 3606
 
5.3%
1 2988
 
4.4%
- 2704
 
4.0%
Other values (195) 25002
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40234
59.0%
Decimal Number 14352
 
21.0%
Space Separator 10891
 
16.0%
Dash Punctuation 2704
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 4273
 
10.6%
동 4001
 
9.9%
구 3816
 
9.5%
시 3688
 
9.2%
특 3606
 
9.0%
별 3606
 
9.0%
울 3606
 
9.0%
강 897
 
2.2%
천 505
 
1.3%
신 402
 
1.0%
Other values (183) 11834
29.4%
Decimal Number
ValueCountFrequency (%)
1 2988
20.8%
2 1803
12.6%
3 1544
10.8%
4 1314
9.2%
5 1308
9.1%
6 1282
8.9%
7 1151
 
8.0%
0 1026
 
7.1%
8 1013
 
7.1%
9 923
 
6.4%
Space Separator
ValueCountFrequency (%)
10891
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2704
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40234
59.0%
Common 27947
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 4273
 
10.6%
동 4001
 
9.9%
구 3816
 
9.5%
시 3688
 
9.2%
특 3606
 
9.0%
별 3606
 
9.0%
울 3606
 
9.0%
강 897
 
2.2%
천 505
 
1.3%
신 402
 
1.0%
Other values (183) 11834
29.4%
Common
ValueCountFrequency (%)
10891
39.0%
1 2988
 
10.7%
- 2704
 
9.7%
2 1803
 
6.5%
3 1544
 
5.5%
4 1314
 
4.7%
5 1308
 
4.7%
6 1282
 
4.6%
7 1151
 
4.1%
0 1026
 
3.7%
Other values (2) 1936
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40234
59.0%
ASCII 27947
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10891
39.0%
1 2988
 
10.7%
- 2704
 
9.7%
2 1803
 
6.5%
3 1544
 
5.5%
4 1314
 
4.7%
5 1308
 
4.7%
6 1282
 
4.6%
7 1151
 
4.1%
0 1026
 
3.7%
Other values (2) 1936
 
6.9%
Hangul
ValueCountFrequency (%)
서 4273
 
10.6%
동 4001
 
9.9%
구 3816
 
9.5%
시 3688
 
9.2%
특 3606
 
9.0%
별 3606
 
9.0%
울 3606
 
9.0%
강 897
 
2.2%
천 505
 
1.3%
신 402
 
1.0%
Other values (183) 11834
29.4%

기타
Text

MISSING 

Distinct47
Distinct (%)52.8%
Missing3517
Missing (%)97.5%
Memory size28.3 KiB
2023-12-11T16:32:33.591377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length33
Mean length8.0337079
Min length2

Characters and Unicode

Total characters715
Distinct characters168
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)48.3%

Sample

1st row공사중
2nd row라모도쇼핑몰이 에이피엠 플레이스로 변경됨
3rd row폐점
4th row공사중
5th row건물 노후화로인한 폐쇄
ValueCountFrequency (%)
공사중 37
 
19.9%
폐점 7
 
3.8%
중 4
 
2.2%
건물 4
 
2.2%
공사 4
 
2.2%
불가 3
 
1.6%
현재 3
 
1.6%
폐쇄 3
 
1.6%
재개발 2
 
1.1%
구역으로 2
 
1.1%
Other values (108) 117
62.9%
2023-12-11T16:32:34.165720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
13.6%
사 57
 
8.0%
중 53
 
7.4%
공 52
 
7.3%
로 16
 
2.2%
2 16
 
2.2%
가 14
 
2.0%
폐 12
 
1.7%
이 11
 
1.5%
일 9
 
1.3%
Other values (158) 378
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 564
78.9%
Space Separator 97
 
13.6%
Decimal Number 36
 
5.0%
Other Punctuation 5
 
0.7%
Dash Punctuation 4
 
0.6%
Open Punctuation 4
 
0.6%
Close Punctuation 4
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 57
 
10.1%
중 53
 
9.4%
공 52
 
9.2%
로 16
 
2.8%
가 14
 
2.5%
폐 12
 
2.1%
이 11
 
2.0%
일 9
 
1.6%
관 9
 
1.6%
인 8
 
1.4%
Other values (145) 323
57.3%
Decimal Number
ValueCountFrequency (%)
2 16
44.4%
1 9
25.0%
0 6
 
16.7%
3 3
 
8.3%
6 1
 
2.8%
5 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 564
78.9%
Common 150
 
21.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 57
 
10.1%
중 53
 
9.4%
공 52
 
9.2%
로 16
 
2.8%
가 14
 
2.5%
폐 12
 
2.1%
이 11
 
2.0%
일 9
 
1.6%
관 9
 
1.6%
인 8
 
1.4%
Other values (145) 323
57.3%
Common
ValueCountFrequency (%)
97
64.7%
2 16
 
10.7%
1 9
 
6.0%
0 6
 
4.0%
- 4
 
2.7%
( 4
 
2.7%
) 4
 
2.7%
3 3
 
2.0%
. 3
 
2.0%
, 2
 
1.3%
Other values (2) 2
 
1.3%
Latin
ValueCountFrequency (%)
X 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 564
78.9%
ASCII 151
 
21.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
64.2%
2 16
 
10.6%
1 9
 
6.0%
0 6
 
4.0%
- 4
 
2.6%
( 4
 
2.6%
) 4
 
2.6%
3 3
 
2.0%
. 3
 
2.0%
, 2
 
1.3%
Other values (3) 3
 
2.0%
Hangul
ValueCountFrequency (%)
사 57
 
10.1%
중 53
 
9.4%
공 52
 
9.2%
로 16
 
2.8%
가 14
 
2.5%
폐 12
 
2.1%
이 11
 
2.0%
일 9
 
1.6%
관 9
 
1.6%
인 8
 
1.4%
Other values (145) 323
57.3%

국가지점번호
Text

Distinct3582
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2023-12-11T16:32:34.697710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters43272
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

Unique3560 ?
Unique (%)98.7%

Sample

1st row다사 5914 6130
2nd row다사 5939 6181
3rd row다사 5989 5275
4th row다사 6014 5247
5th row다사 6092 5204
ValueCountFrequency (%)
다사 3606
33.3%
5132 11
 
0.1%
5799 10
 
0.1%
4718 10
 
0.1%
4477 9
 
0.1%
4372 9
 
0.1%
4711 9
 
0.1%
4673 9
 
0.1%
5090 9
 
0.1%
4914 9
 
0.1%
Other values (2613) 7127
65.9%
2023-12-11T16:32:35.419939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7212
16.7%
4 5214
12.0%
5 4596
10.6%
다 3606
8.3%
사 3606
8.3%
6 3408
7.9%
7 2347
 
5.4%
1 2330
 
5.4%
2 2276
 
5.3%
3 2268
 
5.2%
Other values (3) 6409
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28848
66.7%
Space Separator 7212
 
16.7%
Other Letter 7212
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 5214
18.1%
5 4596
15.9%
6 3408
11.8%
7 2347
8.1%
1 2330
8.1%
2 2276
7.9%
3 2268
7.9%
9 2170
7.5%
8 2159
7.5%
0 2080
 
7.2%
Other Letter
ValueCountFrequency (%)
다 3606
50.0%
사 3606
50.0%
Space Separator
ValueCountFrequency (%)
7212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36060
83.3%
Hangul 7212
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
7212
20.0%
4 5214
14.5%
5 4596
12.7%
6 3408
9.5%
7 2347
 
6.5%
1 2330
 
6.5%
2 2276
 
6.3%
3 2268
 
6.3%
9 2170
 
6.0%
8 2159
 
6.0%
Hangul
ValueCountFrequency (%)
다 3606
50.0%
사 3606
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36060
83.3%
Hangul 7212
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7212
20.0%
4 5214
14.5%
5 4596
12.7%
6 3408
9.5%
7 2347
 
6.5%
1 2330
 
6.5%
2 2276
 
6.3%
3 2268
 
6.3%
9 2170
 
6.0%
8 2159
 
6.0%
Hangul
ValueCountFrequency (%)
다 3606
50.0%
사 3606
50.0%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
Minimum2022-12-07 00:00:00
Maximum2022-12-07 00:00:00
2023-12-11T16:32:35.586775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:35.733492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T16:32:25.222860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:24.228323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:24.722205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:25.376860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:24.384677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:24.883999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:25.557714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:24.545092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:32:25.045005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T16:32:35.880342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디위도경도건물군여부시설용도분류기타
아이디1.0000.5130.4810.4550.9450.813
위도0.5131.0000.6510.1830.3810.623
경도0.4810.6511.0000.1680.4210.000
건물군여부0.4550.1830.1681.0000.4740.948
시설용도분류0.9450.3810.4210.4741.0000.993
기타0.8130.6230.0000.9480.9931.000
2023-12-11T16:32:36.038938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설용도분류건물군여부
시설용도분류1.0000.323
건물군여부0.3231.000
2023-12-11T16:32:36.188461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디위도경도건물군여부시설용도분류
아이디1.000-0.042-0.0370.3070.605
위도-0.0421.0000.1370.1100.125
경도-0.0370.1371.0000.1010.141
건물군여부0.3070.1100.1011.0000.323
시설용도분류0.6050.1250.1410.3231.000

Missing values

2023-12-11T16:32:25.832837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T16:32:26.197281image/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.
2023-12-11T16:32:26.405062image/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

아이디새주소 아이디시설 아이디시설명위도경도건물군여부시설용도분류소재지 도로명주소소재지 지번주소기타국가지점번호데이터 기준일자
03007<NA>P0877꿈동산어린이공원37.650288127.03686BG_AAFU_BI서울특별시 도봉구 도봉로110나길 99서울특별시 도봉구 창동 663-1<NA>다사 5914 61302022-12-07 00:00:00.0
13008<NA>P0878미화어린이공원37.654945127.03969BG_AAFU_BI서울특별시 도봉구 도봉로 564서울특별시 도봉구 창동 715-17<NA>다사 5939 61812022-12-07 00:00:00.0
23009<NA>P0879꿈동산어린이공원37.57329127.04584BG_AAFU_BI서울특별시 동대문구 황물로 42서울특별시 동대문구 답십리동 1002-1<NA>다사 5989 52752022-12-07 00:00:00.0
33010<NA>P0880새움어린이공원37.57076127.048676BG_AAFU_BI서울특별시 동대문구 천호대로55길 11서울특별시 동대문구 답십리동 1009-1<NA>다사 6014 52472022-12-07 00:00:00.0
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53013<NA>P0883우산각어린이공원37.57345127.02443BG_AAFU_BI서울특별시 동대문구 천호대로4길 22서울특별시 동대문구 신설동 109-4<NA>다사 5800 52782022-12-07 00:00:00.0
631<NA>B0031주양쇼핑37.55252127.153496BG_ABFU_BA서울특별시 강동구 고덕로62길 55서울특별시 강동구 명일동 48공사중다사 6939 50402022-12-07 00:00:00.0
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아이디새주소 아이디시설 아이디시설명위도경도건물군여부시설용도분류소재지 도로명주소소재지 지번주소기타국가지점번호데이터 기준일자
35963128<NA>P0998궁뜰어린이공원37.56901126.930405BG_AAFU_BI서울특별시 서대문구 연희로15안길 17서울특별시 서대문구 연희동 123-5<NA>다사 4969 52332022-12-07 00:00:00.0
35973189<NA>P1059가온공원37.453815127.05906BG_AAFU_BI서울특별시 서초구 헌릉로8길 22서울특별시 서초구 신원동 572<NA>다사 6100 39492022-12-07 00:00:00.0
35983191<NA>P1061세원공원37.455933127.049934BG_AAFU_BI서울특별시 서초구 청계산로 91서울특별시 서초구 신원동 500-5<NA>다사 6019 39732022-12-07 00:00:00.0
35993210<NA>P1080식유촌공원37.45821127.01358BG_AAFU_BI서울특별시 서초구 식유촌길 39서울특별시 서초구 우면동 596-3<NA>다사 5698 40002022-12-07 00:00:00.0
36001881<NA>B1882편한정형외과의원37.501667127.108665BG_AAFU_BE서울특별시 송파구 가락로 113서울특별시 송파구 석촌동 295-10<NA>다사 6541 44782022-12-07 00:00:00.0
36011894<NA>B1895연희연세치과의원37.562363126.92789BG_AAFU_BE서울특별시 서대문구 연희로 42서울특별시 서대문구 연희동 353-100<NA>다사 4947 51592022-12-07 00:00:00.0
36021908<NA>B1909바르다권치과의원37.48324126.90508BG_AAFU_BE서울특별시 관악구 조원로 24서울특별시 관악구 신림동 1653-6<NA>다사 4740 42832022-12-07 00:00:00.0
36033398<NA>P1268푸른어린이공원37.511242126.83787BG_AAFU_BI서울특별시 양천구 신정로11길 63서울특별시 양천구 신정동 1283-1<NA>다사 4148 45972022-12-07 00:00:00.0
36043454<NA>P1324돌모루어린이공원37.54293126.96846BG_AAFU_BI서울특별시 용산구 원효로97길 50서울특별시 용산구 청파동3가 118-102<NA>다사 5304 49422022-12-07 00:00:00.0
36053497<NA>P1367신문로공원37.569057126.97241BG_AAFU_BI서울특별시 종로구 새문안로2길 10서울특별시 종로구 신문로2가 160-1<NA>다사 5340 52312022-12-07 00:00:00.0