Overview

Dataset statistics

Number of variables9
Number of observations8622
Missing cells525
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory648.5 KiB
Average record size in memory77.0 B

Variable types

Numeric5
Text3
Categorical1

Dataset

Description공간정보관리번호,X 좌표 최소값,Y 좌표 최소값,X 좌표 최대값,Y 좌표 최대값,관리번호,관리기관명,위치상세내용,비고
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-1255/S/1/datasetView.do

Alerts

공간정보관리번호 is highly overall correlated with 관리기관명High correlation
X 좌표 최소값 is highly overall correlated with X 좌표 최대값 and 1 other fieldsHigh correlation
Y 좌표 최소값 is highly overall correlated with Y 좌표 최대값 and 1 other fieldsHigh correlation
X 좌표 최대값 is highly overall correlated with X 좌표 최소값 and 1 other fieldsHigh correlation
Y 좌표 최대값 is highly overall correlated with Y 좌표 최소값 and 1 other fieldsHigh correlation
관리기관명 is highly overall correlated with 공간정보관리번호 and 4 other fieldsHigh correlation
비고 has 525 (6.1%) missing valuesMissing
공간정보관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-11 04:15:19.765375
Analysis finished2024-05-11 04:15:33.353433
Duration13.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct8622
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4352.4326
Minimum1
Maximum8886
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.9 KiB
2024-05-11T04:15:33.670460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile432.05
Q12156.25
median4329.5
Q36537.75
95-th percentile8295.95
Maximum8886
Range8885
Interquartile range (IQR)4381.5

Descriptive statistics

Standard deviation2528.38
Coefficient of variation (CV)0.58091191
Kurtosis-1.2053945
Mean4352.4326
Median Absolute Deviation (MAD)2191
Skewness0.009843911
Sum37526674
Variance6392705.2
MonotonicityStrictly increasing
2024-05-11T04:15:34.348489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5808 1
 
< 0.1%
5822 1
 
< 0.1%
5821 1
 
< 0.1%
5820 1
 
< 0.1%
5819 1
 
< 0.1%
5818 1
 
< 0.1%
5817 1
 
< 0.1%
5816 1
 
< 0.1%
5815 1
 
< 0.1%
Other values (8612) 8612
99.9%
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 (%)
8886 1
< 0.1%
8885 1
< 0.1%
8884 1
< 0.1%
8882 1
< 0.1%
8881 1
< 0.1%
8861 1
< 0.1%
8841 1
< 0.1%
8821 1
< 0.1%
8820 1
< 0.1%
8818 1
< 0.1%

X 좌표 최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct8380
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197652.24
Minimum182348
Maximum215738.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.9 KiB
2024-05-11T04:15:34.775455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182348
5-th percentile186630.3
Q1192844.08
median196864
Q3202707.07
95-th percentile208244.15
Maximum215738.8
Range33390.8
Interquartile range (IQR)9863

Descriptive statistics

Standard deviation6671.1491
Coefficient of variation (CV)0.033751953
Kurtosis-0.65397485
Mean197652.24
Median Absolute Deviation (MAD)4943
Skewness0.11986858
Sum1.7041576 × 109
Variance44504231
MonotonicityNot monotonic
2024-05-11T04:15:35.319964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202030.0 4
 
< 0.1%
191397.1 3
 
< 0.1%
187566.0 3
 
< 0.1%
193955.5 3
 
< 0.1%
186200.0 3
 
< 0.1%
204165.6 3
 
< 0.1%
201615.7 3
 
< 0.1%
207311.1 3
 
< 0.1%
186122.0 3
 
< 0.1%
204927.3 3
 
< 0.1%
Other values (8370) 8591
99.6%
ValueCountFrequency (%)
182348.0 1
< 0.1%
182350.0 1
< 0.1%
182502.0 1
< 0.1%
182532.0 1
< 0.1%
182542.0 1
< 0.1%
182555.0 1
< 0.1%
182838.0 1
< 0.1%
182950.0 1
< 0.1%
183026.0 1
< 0.1%
183058.0 1
< 0.1%
ValueCountFrequency (%)
215738.8 1
< 0.1%
215563.0 1
< 0.1%
215277.2 1
< 0.1%
215244.1 1
< 0.1%
215236.7 1
< 0.1%
215209.1 1
< 0.1%
215205.2 1
< 0.1%
215185.1 1
< 0.1%
215171.3 1
< 0.1%
215155.3 1
< 0.1%

Y 좌표 최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct8296
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean549447.54
Minimum537245.4
Maximum565482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.9 KiB
2024-05-11T04:15:35.792994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum537245.4
5-th percentile540994.49
Q1544466.65
median549634.65
Q3553939.23
95-th percentile558588.07
Maximum565482
Range28236.6
Interquartile range (IQR)9472.575

Descriptive statistics

Standard deviation5766.7707
Coefficient of variation (CV)0.01049558
Kurtosis-0.76480251
Mean549447.54
Median Absolute Deviation (MAD)4777.4
Skewness0.22432452
Sum4.7373367 × 109
Variance33255645
MonotonicityNot monotonic
2024-05-11T04:15:36.274300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
550689.0 4
 
< 0.1%
558295.8 4
 
< 0.1%
551203.0 4
 
< 0.1%
556931.0 3
 
< 0.1%
548634.0 3
 
< 0.1%
549954.0 3
 
< 0.1%
550667.0 3
 
< 0.1%
554047.2 3
 
< 0.1%
550353.0 2
 
< 0.1%
548493.0 2
 
< 0.1%
Other values (8286) 8591
99.6%
ValueCountFrequency (%)
537245.4 1
< 0.1%
537246.2 1
< 0.1%
537254.4 1
< 0.1%
537288.2 1
< 0.1%
537299.1 1
< 0.1%
537334.1 1
< 0.1%
537355.9 1
< 0.1%
537560.4 1
< 0.1%
537726.9 1
< 0.1%
537745.9 1
< 0.1%
ValueCountFrequency (%)
565482.0 1
< 0.1%
565354.1 1
< 0.1%
565321.3 1
< 0.1%
565170.4 1
< 0.1%
564466.4 1
< 0.1%
564435.7 1
< 0.1%
564286.0 1
< 0.1%
564225.5 1
< 0.1%
564222.5 1
< 0.1%
564182.3 1
< 0.1%

X 좌표 최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct8380
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197652.24
Minimum182348
Maximum215738.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.9 KiB
2024-05-11T04:15:36.867735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182348
5-th percentile186630.3
Q1192844.08
median196864
Q3202707.07
95-th percentile208244.15
Maximum215738.8
Range33390.8
Interquartile range (IQR)9863

Descriptive statistics

Standard deviation6671.1491
Coefficient of variation (CV)0.033751953
Kurtosis-0.65397485
Mean197652.24
Median Absolute Deviation (MAD)4943
Skewness0.11986858
Sum1.7041576 × 109
Variance44504231
MonotonicityNot monotonic
2024-05-11T04:15:37.378235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202030.0 4
 
< 0.1%
191397.1 3
 
< 0.1%
187566.0 3
 
< 0.1%
193955.5 3
 
< 0.1%
186200.0 3
 
< 0.1%
204165.6 3
 
< 0.1%
201615.7 3
 
< 0.1%
207311.1 3
 
< 0.1%
186122.0 3
 
< 0.1%
204927.3 3
 
< 0.1%
Other values (8370) 8591
99.6%
ValueCountFrequency (%)
182348.0 1
< 0.1%
182350.0 1
< 0.1%
182502.0 1
< 0.1%
182532.0 1
< 0.1%
182542.0 1
< 0.1%
182555.0 1
< 0.1%
182838.0 1
< 0.1%
182950.0 1
< 0.1%
183026.0 1
< 0.1%
183058.0 1
< 0.1%
ValueCountFrequency (%)
215738.8 1
< 0.1%
215563.0 1
< 0.1%
215277.2 1
< 0.1%
215244.1 1
< 0.1%
215236.7 1
< 0.1%
215209.1 1
< 0.1%
215205.2 1
< 0.1%
215185.1 1
< 0.1%
215171.3 1
< 0.1%
215155.3 1
< 0.1%

Y 좌표 최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct8296
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean549447.54
Minimum537245.4
Maximum565482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.9 KiB
2024-05-11T04:15:37.887810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum537245.4
5-th percentile540994.49
Q1544466.65
median549634.65
Q3553939.23
95-th percentile558588.07
Maximum565482
Range28236.6
Interquartile range (IQR)9472.575

Descriptive statistics

Standard deviation5766.7707
Coefficient of variation (CV)0.01049558
Kurtosis-0.76480251
Mean549447.54
Median Absolute Deviation (MAD)4777.4
Skewness0.22432452
Sum4.7373367 × 109
Variance33255645
MonotonicityNot monotonic
2024-05-11T04:15:38.438602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
550689.0 4
 
< 0.1%
558295.8 4
 
< 0.1%
551203.0 4
 
< 0.1%
556931.0 3
 
< 0.1%
548634.0 3
 
< 0.1%
549954.0 3
 
< 0.1%
550667.0 3
 
< 0.1%
554047.2 3
 
< 0.1%
550353.0 2
 
< 0.1%
548493.0 2
 
< 0.1%
Other values (8286) 8591
99.6%
ValueCountFrequency (%)
537245.4 1
< 0.1%
537246.2 1
< 0.1%
537254.4 1
< 0.1%
537288.2 1
< 0.1%
537299.1 1
< 0.1%
537334.1 1
< 0.1%
537355.9 1
< 0.1%
537560.4 1
< 0.1%
537726.9 1
< 0.1%
537745.9 1
< 0.1%
ValueCountFrequency (%)
565482.0 1
< 0.1%
565354.1 1
< 0.1%
565321.3 1
< 0.1%
565170.4 1
< 0.1%
564466.4 1
< 0.1%
564435.7 1
< 0.1%
564286.0 1
< 0.1%
564225.5 1
< 0.1%
564222.5 1
< 0.1%
564182.3 1
< 0.1%

관리번호
Text

Distinct8592
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
2024-05-11T04:15:38.930861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.6165623
Min length4

Characters and Unicode

Total characters57048
Distinct characters161
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8576 ?
Unique (%)99.5%

Sample

1st row혜화동-001
2nd row혜화동-018
3rd row혜화동-013
4th row혜화동-019
5th row부암동-016
ValueCountFrequency (%)
305
 
3.3%
구로2 57
 
0.6%
고척1 35
 
0.4%
가리봉 35
 
0.4%
오류1 35
 
0.4%
수궁 35
 
0.4%
오류2 35
 
0.4%
구로5 28
 
0.3%
고척2 25
 
0.3%
개봉3 20
 
0.2%
Other values (8305) 8677
93.4%
2024-05-11T04:15:39.899488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 8515
14.9%
0 6491
 
11.4%
1 4778
 
8.4%
동 4336
 
7.6%
2 3724
 
6.5%
3 2450
 
4.3%
4 2076
 
3.6%
5 1473
 
2.6%
6 1276
 
2.2%
7 1169
 
2.0%
Other values (151) 20760
36.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25628
44.9%
Other Letter 22218
38.9%
Dash Punctuation 8515
 
14.9%
Space Separator 665
 
1.2%
Other Punctuation 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4336
 
19.5%
대 905
 
4.1%
서 868
 
3.9%
산 791
 
3.6%
구 736
 
3.3%
문 716
 
3.2%
성 650
 
2.9%
작 499
 
2.2%
양 458
 
2.1%
용 427
 
1.9%
Other values (138) 11832
53.3%
Decimal Number
ValueCountFrequency (%)
0 6491
25.3%
1 4778
18.6%
2 3724
14.5%
3 2450
 
9.6%
4 2076
 
8.1%
5 1473
 
5.7%
6 1276
 
5.0%
7 1169
 
4.6%
8 1147
 
4.5%
9 1044
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 8515
100.0%
Space Separator
ValueCountFrequency (%)
665
100.0%
Other Punctuation
ValueCountFrequency (%)
. 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34830
61.1%
Hangul 22218
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4336
 
19.5%
대 905
 
4.1%
서 868
 
3.9%
산 791
 
3.6%
구 736
 
3.3%
문 716
 
3.2%
성 650
 
2.9%
작 499
 
2.2%
양 458
 
2.1%
용 427
 
1.9%
Other values (138) 11832
53.3%
Common
ValueCountFrequency (%)
- 8515
24.4%
0 6491
18.6%
1 4778
13.7%
2 3724
10.7%
3 2450
 
7.0%
4 2076
 
6.0%
5 1473
 
4.2%
6 1276
 
3.7%
7 1169
 
3.4%
8 1147
 
3.3%
Other values (3) 1731
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34830
61.1%
Hangul 22218
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 8515
24.4%
0 6491
18.6%
1 4778
13.7%
2 3724
10.7%
3 2450
 
7.0%
4 2076
 
6.0%
5 1473
 
4.2%
6 1276
 
3.7%
7 1169
 
3.4%
8 1147
 
3.3%
Other values (3) 1731
 
5.0%
Hangul
ValueCountFrequency (%)
동 4336
 
19.5%
대 905
 
4.1%
서 868
 
3.9%
산 791
 
3.6%
구 736
 
3.3%
문 716
 
3.2%
성 650
 
2.9%
작 499
 
2.2%
양 458
 
2.1%
용 427
 
1.9%
Other values (138) 11832
53.3%

관리기관명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
서대문구
644 
관악구
633 
강남구
626 
성북구
 
539
동작구
 
499
Other values (20)
5681 

Length

Max length4
Median length3
Mean length3.1017165
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서대문구 644
 
7.5%
관악구 633
 
7.3%
강남구 626
 
7.3%
성북구 539
 
6.3%
동작구 499
 
5.8%
은평구 467
 
5.4%
구로구 445
 
5.2%
마포구 411
 
4.8%
용산구 403
 
4.7%
서초구 387
 
4.5%
Other values (15) 3568
41.4%

Length

2024-05-11T04:15:40.492625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서대문구 644
 
7.5%
관악구 633
 
7.3%
강남구 626
 
7.3%
성북구 539
 
6.3%
동작구 499
 
5.8%
은평구 467
 
5.4%
구로구 445
 
5.2%
마포구 411
 
4.8%
용산구 403
 
4.7%
서초구 387
 
4.5%
Other values (15) 3568
41.4%

위치상세내용
Text

Distinct8428
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
2024-05-11T04:15:41.366392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length10.469497
Min length3

Characters and Unicode

Total characters90268
Distinct characters452
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8264 ?
Unique (%)95.8%

Sample

1st row명륜8길
2nd row창경궁로35길
3rd row성균관로14길
4th row혜화로5길
5th row세검정로 227-8
ValueCountFrequency (%)
12 136
 
0.7%
15 126
 
0.7%
8 124
 
0.7%
9 123
 
0.7%
22 123
 
0.7%
16 122
 
0.7%
7 121
 
0.7%
21 121
 
0.7%
11 119
 
0.6%
24 118
 
0.6%
Other values (6776) 17264
93.3%
2024-05-11T04:15:43.513061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10232
 
11.3%
로 7727
 
8.6%
길 7399
 
8.2%
1 7184
 
8.0%
2 5642
 
6.3%
3 4096
 
4.5%
4 3476
 
3.9%
5 3004
 
3.3%
6 2780
 
3.1%
7 2659
 
2.9%
Other values (442) 36069
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42002
46.5%
Decimal Number 35363
39.2%
Space Separator 10234
 
11.3%
Dash Punctuation 2135
 
2.4%
Close Punctuation 227
 
0.3%
Open Punctuation 227
 
0.3%
Other Punctuation 40
 
< 0.1%
Uppercase Letter 30
 
< 0.1%
Math Symbol 5
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 7727
 
18.4%
길 7399
 
17.6%
대 922
 
2.2%
가 918
 
2.2%
산 867
 
2.1%
동 863
 
2.1%
나 428
 
1.0%
마 395
 
0.9%
봉 390
 
0.9%
신 380
 
0.9%
Other values (407) 21713
51.7%
Decimal Number
ValueCountFrequency (%)
1 7184
20.3%
2 5642
16.0%
3 4096
11.6%
4 3476
9.8%
5 3004
8.5%
6 2780
 
7.9%
7 2659
 
7.5%
0 2309
 
6.5%
8 2271
 
6.4%
9 1942
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
C 10
33.3%
T 4
 
13.3%
A 4
 
13.3%
V 4
 
13.3%
S 2
 
6.7%
B 2
 
6.7%
U 2
 
6.7%
K 1
 
3.3%
H 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 22
55.0%
, 14
35.0%
& 2
 
5.0%
＠ 1
 
2.5%
@ 1
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
c 1
25.0%
m 1
25.0%
d 1
25.0%
Space Separator
ValueCountFrequency (%)
10232
> 99.9%
　 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 227
100.0%
Open Punctuation
ValueCountFrequency (%)
( 227
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48232
53.4%
Hangul 42002
46.5%
Latin 34
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 7727
 
18.4%
길 7399
 
17.6%
대 922
 
2.2%
가 918
 
2.2%
산 867
 
2.1%
동 863
 
2.1%
나 428
 
1.0%
마 395
 
0.9%
봉 390
 
0.9%
신 380
 
0.9%
Other values (407) 21713
51.7%
Common
ValueCountFrequency (%)
10232
21.2%
1 7184
14.9%
2 5642
11.7%
3 4096
8.5%
4 3476
 
7.2%
5 3004
 
6.2%
6 2780
 
5.8%
7 2659
 
5.5%
0 2309
 
4.8%
8 2271
 
4.7%
Other values (12) 4579
9.5%
Latin
ValueCountFrequency (%)
C 10
29.4%
T 4
 
11.8%
A 4
 
11.8%
V 4
 
11.8%
S 2
 
5.9%
B 2
 
5.9%
U 2
 
5.9%
e 1
 
2.9%
c 1
 
2.9%
m 1
 
2.9%
Other values (3) 3
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48263
53.5%
Hangul 41991
46.5%
Compat Jamo 11
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10232
21.2%
1 7184
14.9%
2 5642
11.7%
3 4096
8.5%
4 3476
 
7.2%
5 3004
 
6.2%
6 2780
 
5.8%
7 2659
 
5.5%
0 2309
 
4.8%
8 2271
 
4.7%
Other values (23) 4610
9.6%
Hangul
ValueCountFrequency (%)
로 7727
 
18.4%
길 7399
 
17.6%
대 922
 
2.2%
가 918
 
2.2%
산 867
 
2.1%
동 863
 
2.1%
나 428
 
1.0%
마 395
 
0.9%
봉 390
 
0.9%
신 380
 
0.9%
Other values (406) 21702
51.7%
Compat Jamo
ValueCountFrequency (%)
ㅡ 11
100.0%
None
ValueCountFrequency (%)
　 2
66.7%
＠ 1
33.3%

비고
Text

MISSING 

Distinct4474
Distinct (%)55.3%
Missing525
Missing (%)6.1%
Memory size67.5 KiB
2024-05-11T04:15:44.855075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length6.4323824
Min length3

Characters and Unicode

Total characters52083
Distinct characters349
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3041 ?
Unique (%)37.6%

Sample

1st row명륜8길
2nd row창경궁로35길
3rd row성균관로14길
4th row혜화로5길
5th row세검정로
ValueCountFrequency (%)
삼양로 77
 
0.8%
덕릉로 51
 
0.5%
인수봉로 49
 
0.5%
오패산로 40
 
0.4%
동일로 40
 
0.4%
개봉2동 34
 
0.4%
상계로 31
 
0.3%
독립문로 31
 
0.3%
용마산로 30
 
0.3%
도봉로 30
 
0.3%
Other values (4342) 9035
95.6%
2024-05-11T04:15:46.615936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 7211
 
13.8%
길 6496
 
12.5%
1 3082
 
5.9%
2 2328
 
4.5%
3 1660
 
3.2%
4 1446
 
2.8%
1365
 
2.6%
5 1210
 
2.3%
6 1036
 
2.0%
7 997
 
1.9%
Other values (339) 25252
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35986
69.1%
Decimal Number 14392
 
27.6%
Space Separator 1367
 
2.6%
Dash Punctuation 217
 
0.4%
Open Punctuation 55
 
0.1%
Close Punctuation 55
 
0.1%
Other Punctuation 8
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 7211
20.0%
길 6496
 
18.1%
가 844
 
2.3%
대 813
 
2.3%
산 781
 
2.2%
동 722
 
2.0%
나 371
 
1.0%
봉 364
 
1.0%
마 349
 
1.0%
서 340
 
0.9%
Other values (319) 17695
49.2%
Decimal Number
ValueCountFrequency (%)
1 3082
21.4%
2 2328
16.2%
3 1660
11.5%
4 1446
10.0%
5 1210
 
8.4%
6 1036
 
7.2%
7 997
 
6.9%
8 997
 
6.9%
0 821
 
5.7%
9 815
 
5.7%
Space Separator
ValueCountFrequency (%)
1365
99.9%
　 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
, 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
D 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 217
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35986
69.1%
Common 16095
30.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 7211
20.0%
길 6496
 
18.1%
가 844
 
2.3%
대 813
 
2.3%
산 781
 
2.2%
동 722
 
2.0%
나 371
 
1.0%
봉 364
 
1.0%
마 349
 
1.0%
서 340
 
0.9%
Other values (319) 17695
49.2%
Common
ValueCountFrequency (%)
1 3082
19.1%
2 2328
14.5%
3 1660
10.3%
4 1446
9.0%
1365
8.5%
5 1210
 
7.5%
6 1036
 
6.4%
7 997
 
6.2%
8 997
 
6.2%
0 821
 
5.1%
Other values (8) 1153
 
7.2%
Latin
ValueCountFrequency (%)
S 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35986
69.1%
ASCII 16095
30.9%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 7211
20.0%
길 6496
 
18.1%
가 844
 
2.3%
대 813
 
2.3%
산 781
 
2.2%
동 722
 
2.0%
나 371
 
1.0%
봉 364
 
1.0%
마 349
 
1.0%
서 340
 
0.9%
Other values (319) 17695
49.2%
ASCII
ValueCountFrequency (%)
1 3082
19.1%
2 2328
14.5%
3 1660
10.3%
4 1446
9.0%
1365
8.5%
5 1210
 
7.5%
6 1036
 
6.4%
7 997
 
6.2%
8 997
 
6.2%
0 821
 
5.1%
Other values (9) 1153
 
7.2%
None
ValueCountFrequency (%)
　 2
100.0%

Interactions

2024-05-11T04:15:30.986286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:23.890783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:25.580311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:27.487392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:29.148371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:31.263001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:24.231517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:25.930995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:27.820520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:29.545819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:31.612568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:24.601099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:26.249915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:28.177757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:29.847805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:31.921565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:24.903523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:26.715711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:28.457768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:30.237429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:32.232064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:25.238028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:27.107234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:28.774991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:15:30.602482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T04:15:47.253679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값관리기관명
공간정보관리번호1.0000.8560.8680.8560.8680.971
X 좌표 최소값0.8561.0000.6111.0000.6110.941
Y 좌표 최소값0.8680.6111.0000.6111.0000.926
X 좌표 최대값0.8561.0000.6111.0000.6110.941
Y 좌표 최대값0.8680.6111.0000.6111.0000.926
관리기관명0.9710.9410.9260.9410.9261.000
2024-05-11T04:15:48.001157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값관리기관명
공간정보관리번호1.0000.214-0.3470.214-0.3470.810
X 좌표 최소값0.2141.0000.2701.0000.2700.699
Y 좌표 최소값-0.3470.2701.0000.2701.0000.656
X 좌표 최대값0.2141.0000.2701.0000.2700.699
Y 좌표 최대값-0.3470.2701.0000.2701.0000.656
관리기관명0.8100.6990.6560.6990.6561.000

Missing values

2024-05-11T04:15:32.649151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T04:15:33.143998image/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

공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값관리번호관리기관명위치상세내용비고
01199387.9554560.1199387.9554560.1혜화동-001종로구명륜8길명륜8길
12200264.0554217.8200264.0554217.8혜화동-018종로구창경궁로35길창경궁로35길
23199781.0554303.7199781.0554303.7혜화동-013종로구성균관로14길성균관로14길
34199918.5554210.0199918.5554210.0혜화동-019종로구혜화로5길혜화로5길
45196287.1555691.5196287.1555691.5부암동-016종로구세검정로 227-8세검정로
56199873.3553990.1199873.3553990.1혜화동-016종로구창경궁로33길창경궁로33길
67196642.6555333.5196642.6555333.5부암동-004종로구자하문로41길 6자하문로41길
78196850.7555300.7196850.7555300.7부암동-011종로구자하문로 252-17자하문로
89199694.6553902.7199694.6553902.7혜화동-022종로구성균관로5길성균관로5길
910196756.2554927.5196756.2554927.5부암동-007종로구창의문로11길 5창의문로11길
공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값관리번호관리기관명위치상세내용비고
86128818201771.1545215.7201771.1545215.7반포1-018서초구주흥길 42<NA>
86138820201665.4544951.4201665.4544951.4반포1-019서초구주흥3길 30<NA>
86148821202003.7545008.8202003.7545008.8반포1-020서초구강남대로79길 31<NA>
86158841193953.4556191.2193953.4556191.2녹번-008은평구녹번로6가길 7<NA>
86168861201809.7545175.0201809.7545175.0반포1-021서초구주흥길 40-19<NA>
86178881208007.7549184.9208007.7549184.9구의3-19광진구구의로10길8<NA>
86188882207907.7552050.8207907.7552050.8중곡4-8광진구용마산로30길62<NA>
86198884207830.9551358.4207830.9551358.4중곡4-31광진구용마산로8가길42<NA>
86208885207832.6551337.7207832.6551337.7중곡4-32광진구용마산로8가길46<NA>
86218886206902.0551168.9206902.0551168.9중곡1-7광진구면목로70<NA>