Overview

Dataset statistics

Number of variables9
Number of observations4989
Missing cells1392
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory375.3 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,제설함번호,관리기관명,위치상세정보,비고
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-1253/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 1388 (27.8%) missing valuesMissing
공간정보관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-11 06:31:48.613605
Analysis finished2024-05-11 06:31:55.476475
Duration6.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct4989
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7157.2177
Minimum4621
Maximum9865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-05-11T15:31:55.592314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4621
5-th percentile4896.4
Q15894
median7143
Q38394
95-th percentile9494.6
Maximum9865
Range5244
Interquartile range (IQR)2500

Descriptive statistics

Standard deviation1465.8633
Coefficient of variation (CV)0.2048091
Kurtosis-1.1466096
Mean7157.2177
Median Absolute Deviation (MAD)1250
Skewness0.04579761
Sum35707359
Variance2148755.3
MonotonicityStrictly increasing
2024-05-11T15:31:55.794167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4621 1
 
< 0.1%
7974 1
 
< 0.1%
7981 1
 
< 0.1%
7980 1
 
< 0.1%
7979 1
 
< 0.1%
7978 1
 
< 0.1%
7977 1
 
< 0.1%
7976 1
 
< 0.1%
7975 1
 
< 0.1%
7973 1
 
< 0.1%
Other values (4979) 4979
99.8%
ValueCountFrequency (%)
4621 1
< 0.1%
4622 1
< 0.1%
4623 1
< 0.1%
4624 1
< 0.1%
4625 1
< 0.1%
4626 1
< 0.1%
4627 1
< 0.1%
4628 1
< 0.1%
4629 1
< 0.1%
4630 1
< 0.1%
ValueCountFrequency (%)
9865 1
< 0.1%
9864 1
< 0.1%
9863 1
< 0.1%
9862 1
< 0.1%
9861 1
< 0.1%
9860 1
< 0.1%
9859 1
< 0.1%
9858 1
< 0.1%
9857 1
< 0.1%
9856 1
< 0.1%

X 좌표 최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct4879
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198600.82
Minimum178629.8
Maximum215855.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-05-11T15:31:55.964268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178629.8
5-th percentile187800.16
Q1194228
median197785.7
Q3203114.7
95-th percentile208681.82
Maximum215855.2
Range37225.4
Interquartile range (IQR)8886.7

Descriptive statistics

Standard deviation6239.812
Coefficient of variation (CV)0.031418862
Kurtosis-0.33543368
Mean198600.82
Median Absolute Deviation (MAD)4491.8
Skewness0.01013867
Sum9.9081951 × 108
Variance38935253
MonotonicityNot monotonic
2024-05-11T15:31:56.144779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208999.9 7
 
0.1%
208693.8 3
 
0.1%
195920.3 2
 
< 0.1%
202105.5 2
 
< 0.1%
192469.4 2
 
< 0.1%
196693.9 2
 
< 0.1%
192422.9 2
 
< 0.1%
202040.4 2
 
< 0.1%
196740.8 2
 
< 0.1%
196398.1 2
 
< 0.1%
Other values (4869) 4963
99.5%
ValueCountFrequency (%)
178629.8 1
< 0.1%
182181.0 1
< 0.1%
182248.0 1
< 0.1%
182297.0 1
< 0.1%
182318.0 1
< 0.1%
182323.0 1
< 0.1%
182391.5 1
< 0.1%
182519.0 1
< 0.1%
182549.7 1
< 0.1%
182768.0 1
< 0.1%
ValueCountFrequency (%)
215855.2 1
< 0.1%
215668.9 1
< 0.1%
215591.0 1
< 0.1%
215334.9 1
< 0.1%
215323.6 1
< 0.1%
215318.8 1
< 0.1%
215270.0 1
< 0.1%
215230.3 1
< 0.1%
215207.2 1
< 0.1%
215114.9 1
< 0.1%

Y 좌표 최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct4878
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean549317.18
Minimum537156.5
Maximum565652.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-05-11T15:31:56.373941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum537156.5
5-th percentile540828.36
Q1543554.8
median549631.2
Q3553753.5
95-th percentile560031.98
Maximum565652.9
Range28496.4
Interquartile range (IQR)10198.7

Descriptive statistics

Standard deviation6158.8556
Coefficient of variation (CV)0.011211839
Kurtosis-0.86909375
Mean549317.18
Median Absolute Deviation (MAD)5127.6
Skewness0.26793504
Sum2.7405434 × 109
Variance37931502
MonotonicityNot monotonic
2024-05-11T15:31:56.877919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
558777.7 7
 
0.1%
558364.9 3
 
0.1%
542425.9 3
 
0.1%
553002.7 2
 
< 0.1%
555447.0 2
 
< 0.1%
553330.6 2
 
< 0.1%
553352.1 2
 
< 0.1%
553298.1 2
 
< 0.1%
553207.1 2
 
< 0.1%
554931.7 2
 
< 0.1%
Other values (4868) 4962
99.5%
ValueCountFrequency (%)
537156.5 1
< 0.1%
537273.4 1
< 0.1%
538148.9 1
< 0.1%
538358.6 1
< 0.1%
538376.1 1
< 0.1%
538398.4 1
< 0.1%
538408.6 1
< 0.1%
538409.1 1
< 0.1%
538551.2 1
< 0.1%
538554.7 1
< 0.1%
ValueCountFrequency (%)
565652.9 1
< 0.1%
565505.0 1
< 0.1%
565478.6 1
< 0.1%
565477.8 1
< 0.1%
565417.6 1
< 0.1%
565295.0 1
< 0.1%
565264.0 1
< 0.1%
565129.6 1
< 0.1%
565118.3 1
< 0.1%
565076.3 1
< 0.1%

X 좌표 최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct4879
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198600.82
Minimum178629.8
Maximum215855.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-05-11T15:31:57.085773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178629.8
5-th percentile187800.16
Q1194228
median197785.7
Q3203114.7
95-th percentile208681.82
Maximum215855.2
Range37225.4
Interquartile range (IQR)8886.7

Descriptive statistics

Standard deviation6239.812
Coefficient of variation (CV)0.031418862
Kurtosis-0.33543368
Mean198600.82
Median Absolute Deviation (MAD)4491.8
Skewness0.01013867
Sum9.9081951 × 108
Variance38935253
MonotonicityNot monotonic
2024-05-11T15:31:57.283566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208999.9 7
 
0.1%
208693.8 3
 
0.1%
195920.3 2
 
< 0.1%
202105.5 2
 
< 0.1%
192469.4 2
 
< 0.1%
196693.9 2
 
< 0.1%
192422.9 2
 
< 0.1%
202040.4 2
 
< 0.1%
196740.8 2
 
< 0.1%
196398.1 2
 
< 0.1%
Other values (4869) 4963
99.5%
ValueCountFrequency (%)
178629.8 1
< 0.1%
182181.0 1
< 0.1%
182248.0 1
< 0.1%
182297.0 1
< 0.1%
182318.0 1
< 0.1%
182323.0 1
< 0.1%
182391.5 1
< 0.1%
182519.0 1
< 0.1%
182549.7 1
< 0.1%
182768.0 1
< 0.1%
ValueCountFrequency (%)
215855.2 1
< 0.1%
215668.9 1
< 0.1%
215591.0 1
< 0.1%
215334.9 1
< 0.1%
215323.6 1
< 0.1%
215318.8 1
< 0.1%
215270.0 1
< 0.1%
215230.3 1
< 0.1%
215207.2 1
< 0.1%
215114.9 1
< 0.1%

Y 좌표 최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct4878
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean549317.18
Minimum537156.5
Maximum565652.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.0 KiB
2024-05-11T15:31:57.489898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum537156.5
5-th percentile540828.36
Q1543554.8
median549631.2
Q3553753.5
95-th percentile560031.98
Maximum565652.9
Range28496.4
Interquartile range (IQR)10198.7

Descriptive statistics

Standard deviation6158.8556
Coefficient of variation (CV)0.011211839
Kurtosis-0.86909375
Mean549317.18
Median Absolute Deviation (MAD)5127.6
Skewness0.26793504
Sum2.7405434 × 109
Variance37931502
MonotonicityNot monotonic
2024-05-11T15:31:57.683959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
558777.7 7
 
0.1%
558364.9 3
 
0.1%
542425.9 3
 
0.1%
553002.7 2
 
< 0.1%
555447.0 2
 
< 0.1%
553330.6 2
 
< 0.1%
553352.1 2
 
< 0.1%
553298.1 2
 
< 0.1%
553207.1 2
 
< 0.1%
554931.7 2
 
< 0.1%
Other values (4868) 4962
99.5%
ValueCountFrequency (%)
537156.5 1
< 0.1%
537273.4 1
< 0.1%
538148.9 1
< 0.1%
538358.6 1
< 0.1%
538376.1 1
< 0.1%
538398.4 1
< 0.1%
538408.6 1
< 0.1%
538409.1 1
< 0.1%
538551.2 1
< 0.1%
538554.7 1
< 0.1%
ValueCountFrequency (%)
565652.9 1
< 0.1%
565505.0 1
< 0.1%
565478.6 1
< 0.1%
565477.8 1
< 0.1%
565417.6 1
< 0.1%
565295.0 1
< 0.1%
565264.0 1
< 0.1%
565129.6 1
< 0.1%
565118.3 1
< 0.1%
565076.3 1
< 0.1%

제설함번호
Text

Distinct4958
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2024-05-11T15:31:58.083769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.186811
Min length1

Characters and Unicode

Total characters30866
Distinct characters102
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4929 ?
Unique (%)98.8%

Sample

1st row가회동 1-001
2nd row가회동 1-002
3rd row가회동 1-003
4th row가회동 1-004
5th row가회동 1-005
ValueCountFrequency (%)
가회동 34
 
0.7%
강동-37 3
 
0.1%
강동-64 3
 
0.1%
이화동 3
 
0.1%
강동-27 2
 
< 0.1%
101 2
 
< 0.1%
강동-80 2
 
< 0.1%
강동-16 2
 
< 0.1%
강동-18 2
 
< 0.1%
056 2
 
< 0.1%
Other values (4950) 4972
98.9%
2024-05-11T15:31:58.821074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4719
15.3%
0 3087
 
10.0%
1 2952
 
9.6%
동 2240
 
7.3%
2 1484
 
4.8%
3 1129
 
3.7%
4 965
 
3.1%
5 959
 
3.1%
6 865
 
2.8%
7 768
 
2.5%
Other values (92) 11698
37.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13630
44.2%
Other Letter 12454
40.3%
Dash Punctuation 4719
 
15.3%
Space Separator 38
 
0.1%
Uppercase Letter 21
 
0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2240
 
18.0%
강 719
 
5.8%
구 623
 
5.0%
성 572
 
4.6%
서 519
 
4.2%
남 376
 
3.0%
북 370
 
3.0%
대 356
 
2.9%
원 307
 
2.5%
부 293
 
2.4%
Other values (76) 6079
48.8%
Decimal Number
ValueCountFrequency (%)
0 3087
22.6%
1 2952
21.7%
2 1484
10.9%
3 1129
 
8.3%
4 965
 
7.1%
5 959
 
7.0%
6 865
 
6.3%
7 768
 
5.6%
8 732
 
5.4%
9 689
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 13
61.9%
A 8
38.1%
Dash Punctuation
ValueCountFrequency (%)
- 4719
100.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18391
59.6%
Hangul 12454
40.3%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2240
 
18.0%
강 719
 
5.8%
구 623
 
5.0%
성 572
 
4.6%
서 519
 
4.2%
남 376
 
3.0%
북 370
 
3.0%
대 356
 
2.9%
원 307
 
2.5%
부 293
 
2.4%
Other values (76) 6079
48.8%
Common
ValueCountFrequency (%)
- 4719
25.7%
0 3087
16.8%
1 2952
16.1%
2 1484
 
8.1%
3 1129
 
6.1%
4 965
 
5.2%
5 959
 
5.2%
6 865
 
4.7%
7 768
 
4.2%
8 732
 
4.0%
Other values (4) 731
 
4.0%
Latin
ValueCountFrequency (%)
B 13
61.9%
A 8
38.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18412
59.7%
Hangul 12454
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4719
25.6%
0 3087
16.8%
1 2952
16.0%
2 1484
 
8.1%
3 1129
 
6.1%
4 965
 
5.2%
5 959
 
5.2%
6 865
 
4.7%
7 768
 
4.2%
8 732
 
4.0%
Other values (6) 752
 
4.1%
Hangul
ValueCountFrequency (%)
동 2240
 
18.0%
강 719
 
5.8%
구 623
 
5.0%
성 572
 
4.6%
서 519
 
4.2%
남 376
 
3.0%
북 370
 
3.0%
대 356
 
2.9%
원 307
 
2.5%
부 293
 
2.4%
Other values (76) 6079
48.8%

관리기관명
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
관악구
800 
종로구
740 
동작구
326 
강남구
299 
노원구
 
200
Other values (29)
2624 

Length

Max length7
Median length3
Mean length3.1908198
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
관악구 800
16.0%
종로구 740
14.8%
동작구 326
 
6.5%
강남구 299
 
6.0%
노원구 200
 
4.0%
성북구 196
 
3.9%
성동구 185
 
3.7%
강북구 168
 
3.4%
동대문구 159
 
3.2%
금천구 153
 
3.1%
Other values (24) 1763
35.3%

Length

2024-05-11T15:31:59.087492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관악구 800
16.0%
종로구 740
14.8%
동작구 326
 
6.5%
강남구 299
 
6.0%
노원구 200
 
4.0%
성북구 196
 
3.9%
성동구 185
 
3.7%
강북구 168
 
3.4%
동대문구 159
 
3.2%
금천구 153
 
3.1%
Other values (24) 1763
35.3%

위치상세정보
Text

Distinct4592
Distinct (%)92.1%
Missing4
Missing (%)0.1%
Memory size39.1 KiB
2024-05-11T15:31:59.514347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length9.2174524
Min length1

Characters and Unicode

Total characters45949
Distinct characters456
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4307 ?
Unique (%)86.4%

Sample

1st row북촌로11나길 10
2nd row북촌로11길 35-7
3rd row북촌로11길 48
4th row북촌로11가길 46
5th row북촌로 94
ValueCountFrequency (%)
앞 120
 
1.3%
입구 49
 
0.5%
도봉로 48
 
0.5%
동일로 39
 
0.4%
천호대로 38
 
0.4%
10 38
 
0.4%
시흥대로 35
 
0.4%
1 31
 
0.3%
16 29
 
0.3%
19 28
 
0.3%
Other values (4268) 9004
95.2%
2024-05-11T15:32:00.158303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4760
 
10.4%
로 3532
 
7.7%
1 3053
 
6.6%
2 2103
 
4.6%
길 2071
 
4.5%
3 1714
 
3.7%
4 1469
 
3.2%
5 1379
 
3.0%
6 1285
 
2.8%
7 1146
 
2.5%
Other values (446) 23437
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24585
53.5%
Decimal Number 14943
32.5%
Space Separator 4760
 
10.4%
Dash Punctuation 798
 
1.7%
Close Punctuation 346
 
0.8%
Open Punctuation 346
 
0.8%
Uppercase Letter 120
 
0.3%
Other Punctuation 23
 
0.1%
Math Symbol 21
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3532
 
14.4%
길 2071
 
8.4%
동 962
 
3.9%
대 523
 
2.1%
산 380
 
1.5%
가 334
 
1.4%
신 322
 
1.3%
교 302
 
1.2%
문 289
 
1.2%
구 260
 
1.1%
Other values (410) 15610
63.5%
Uppercase Letter
ValueCountFrequency (%)
C 36
30.0%
I 31
25.8%
P 9
 
7.5%
U 9
 
7.5%
T 5
 
4.2%
M 5
 
4.2%
D 5
 
4.2%
K 5
 
4.2%
S 4
 
3.3%
G 3
 
2.5%
Other values (4) 8
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 3053
20.4%
2 2103
14.1%
3 1714
11.5%
4 1469
9.8%
5 1379
9.2%
6 1285
8.6%
7 1146
 
7.7%
0 1008
 
6.7%
8 903
 
6.0%
9 883
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 12
52.2%
. 6
26.1%
@ 5
21.7%
Math Symbol
ValueCountFrequency (%)
→ 14
66.7%
~ 7
33.3%
Lowercase Letter
ValueCountFrequency (%)
c 3
50.0%
i 3
50.0%
Space Separator
ValueCountFrequency (%)
4760
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 798
100.0%
Close Punctuation
ValueCountFrequency (%)
) 346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 346
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24585
53.5%
Common 21238
46.2%
Latin 126
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3532
 
14.4%
길 2071
 
8.4%
동 962
 
3.9%
대 523
 
2.1%
산 380
 
1.5%
가 334
 
1.4%
신 322
 
1.3%
교 302
 
1.2%
문 289
 
1.2%
구 260
 
1.1%
Other values (410) 15610
63.5%
Common
ValueCountFrequency (%)
4760
22.4%
1 3053
14.4%
2 2103
9.9%
3 1714
 
8.1%
4 1469
 
6.9%
5 1379
 
6.5%
6 1285
 
6.1%
7 1146
 
5.4%
0 1008
 
4.7%
8 903
 
4.3%
Other values (10) 2418
11.4%
Latin
ValueCountFrequency (%)
C 36
28.6%
I 31
24.6%
P 9
 
7.1%
U 9
 
7.1%
T 5
 
4.0%
M 5
 
4.0%
D 5
 
4.0%
K 5
 
4.0%
S 4
 
3.2%
c 3
 
2.4%
Other values (6) 14
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24585
53.5%
ASCII 21350
46.5%
Arrows 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4760
22.3%
1 3053
14.3%
2 2103
9.9%
3 1714
 
8.0%
4 1469
 
6.9%
5 1379
 
6.5%
6 1285
 
6.0%
7 1146
 
5.4%
0 1008
 
4.7%
8 903
 
4.2%
Other values (25) 2530
11.9%
Hangul
ValueCountFrequency (%)
로 3532
 
14.4%
길 2071
 
8.4%
동 962
 
3.9%
대 523
 
2.1%
산 380
 
1.5%
가 334
 
1.4%
신 322
 
1.3%
교 302
 
1.2%
문 289
 
1.2%
구 260
 
1.1%
Other values (410) 15610
63.5%
Arrows
ValueCountFrequency (%)
→ 14
100.0%

비고
Text

MISSING 

Distinct1122
Distinct (%)31.2%
Missing1388
Missing (%)27.8%
Memory size39.1 KiB
2024-05-11T15:32:00.602842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length4.8058873
Min length1

Characters and Unicode

Total characters17306
Distinct characters334
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique619 ?
Unique (%)17.2%

Sample

1st row북촌로11나길
2nd row북촌로11길
3rd row북촌로11길
4th row북촌로11가길
5th row북촌로
ValueCountFrequency (%)
앞 60
 
1.5%
천호대로 59
 
1.4%
삼양로 50
 
1.2%
남부순환로 43
 
1.1%
동일로 41
 
1.0%
망우로 35
 
0.9%
공항대로 34
 
0.8%
시흥대로 34
 
0.8%
영등포구 33
 
0.8%
강남대로 27
 
0.7%
Other values (1250) 3679
89.8%
2024-05-11T15:32:01.362206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 2894
 
16.7%
길 986
 
5.7%
동 571
 
3.3%
501
 
2.9%
대 495
 
2.9%
1 430
 
2.5%
2 311
 
1.8%
3 289
 
1.7%
산 243
 
1.4%
5 237
 
1.4%
Other values (324) 10349
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14506
83.8%
Decimal Number 2065
 
11.9%
Space Separator 501
 
2.9%
Dash Punctuation 67
 
0.4%
Open Punctuation 60
 
0.3%
Close Punctuation 60
 
0.3%
Uppercase Letter 32
 
0.2%
Lowercase Letter 8
 
< 0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 2894
 
20.0%
길 986
 
6.8%
동 571
 
3.9%
대 495
 
3.4%
산 243
 
1.7%
가 189
 
1.3%
도 175
 
1.2%
양 155
 
1.1%
봉 154
 
1.1%
문 147
 
1.0%
Other values (299) 8497
58.6%
Decimal Number
ValueCountFrequency (%)
1 430
20.8%
2 311
15.1%
3 289
14.0%
5 237
11.5%
4 230
11.1%
6 181
8.8%
7 114
 
5.5%
0 94
 
4.6%
9 91
 
4.4%
8 88
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 9
28.1%
I 9
28.1%
G 4
12.5%
S 4
12.5%
A 2
 
6.2%
O 1
 
3.1%
B 1
 
3.1%
U 1
 
3.1%
R 1
 
3.1%
Space Separator
ValueCountFrequency (%)
501
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14506
83.8%
Common 2760
 
15.9%
Latin 40
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 2894
 
20.0%
길 986
 
6.8%
동 571
 
3.9%
대 495
 
3.4%
산 243
 
1.7%
가 189
 
1.3%
도 175
 
1.2%
양 155
 
1.1%
봉 154
 
1.1%
문 147
 
1.0%
Other values (299) 8497
58.6%
Common
ValueCountFrequency (%)
501
18.2%
1 430
15.6%
2 311
11.3%
3 289
10.5%
5 237
8.6%
4 230
8.3%
6 181
 
6.6%
7 114
 
4.1%
0 94
 
3.4%
9 91
 
3.3%
Other values (5) 282
10.2%
Latin
ValueCountFrequency (%)
C 9
22.5%
I 9
22.5%
a 8
20.0%
G 4
10.0%
S 4
10.0%
A 2
 
5.0%
O 1
 
2.5%
B 1
 
2.5%
U 1
 
2.5%
R 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14506
83.8%
ASCII 2800
 
16.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 2894
 
20.0%
길 986
 
6.8%
동 571
 
3.9%
대 495
 
3.4%
산 243
 
1.7%
가 189
 
1.3%
도 175
 
1.2%
양 155
 
1.1%
봉 154
 
1.1%
문 147
 
1.0%
Other values (299) 8497
58.6%
ASCII
ValueCountFrequency (%)
501
17.9%
1 430
15.4%
2 311
11.1%
3 289
10.3%
5 237
8.5%
4 230
8.2%
6 181
 
6.5%
7 114
 
4.1%
0 94
 
3.4%
9 91
 
3.2%
Other values (15) 322
11.5%

Interactions

2024-05-11T15:31:54.106561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:50.397699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:51.272244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:52.306497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:53.145615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:54.280452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:50.557830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:51.466380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:52.464090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:53.324407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:54.465346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:50.715566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:51.692179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:52.624809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:53.517246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:54.635154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:50.887732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:51.882938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:52.766080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:53.703300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:54.774078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:51.079537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:52.112196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:52.952112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:31:53.896484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:32:01.520445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값관리기관명
공간정보관리번호1.0000.7740.8340.7740.8340.959
X 좌표 최소값0.7741.0000.6301.0000.6300.916
Y 좌표 최소값0.8340.6301.0000.6301.0000.923
X 좌표 최대값0.7741.0000.6301.0000.6300.916
Y 좌표 최대값0.8340.6301.0000.6301.0000.923
관리기관명0.9590.9160.9230.9160.9231.000
2024-05-11T15:32:01.683255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값관리기관명
공간정보관리번호1.000-0.208-0.433-0.208-0.4330.766
X 좌표 최소값-0.2081.0000.4021.0000.4020.634
Y 좌표 최소값-0.4330.4021.0000.4021.0000.652
X 좌표 최대값-0.2081.0000.4021.0000.4020.634
Y 좌표 최대값-0.4330.4021.0000.4021.0000.652
관리기관명0.7660.6340.6520.6340.6521.000

Missing values

2024-05-11T15:31:54.972212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:31:55.209701image/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.
2024-05-11T15:31:55.391588image/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

공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값제설함번호관리기관명위치상세정보비고
04621198511.6553626.4198511.6553626.4가회동 1-001종로구북촌로11나길 10북촌로11나길
14622198510.6553653.5198510.6553653.5가회동 1-002종로구북촌로11길 35-7북촌로11길
24623198545.8553706.0198545.8553706.0가회동 1-003종로구북촌로11길 48북촌로11길
34624198566.0553769.0198566.0553769.0가회동 1-004종로구북촌로11가길 46북촌로11가길
44625198704.4553963.2198704.4553963.2가회동 1-005종로구북촌로 94북촌로
54626198732.5553742.7198732.5553742.7가회동 1-006종로구창덕궁길 189창덕궁길
64627198846.4553722.0198846.4553722.0가회동 1-008종로구계동길 128계동길
74628198799.6553737.3198799.6553737.3가회동 1-007종로구창덕궁길 174창덕궁길
84629198890.4553730.3198890.4553730.3가회동 1-009종로구창덕궁길 152창덕궁길
94630198953.3553729.1198953.3553729.1가회동 1-010종로구창덕궁길 144창덕궁길
공간정보관리번호X 좌표 최소값Y 좌표 최소값X 좌표 최대값Y 좌표 최대값제설함번호관리기관명위치상세정보비고
49799856196733.9554440.0196733.9554440.0부암동-160종로구창의문로5길44<NA>
49809857196760.2554439.8196760.2554439.8부암동-161종로구창의문로5길41<NA>
49819858196821.9554423.4196821.9554423.4부암동-163종로구창의문로5길57<NA>
49829859196792.5554378.5196792.5554378.5부암동-164종로구창의문로5길53<NA>
49839860196820.4554602.5196820.4554602.5부암동-165종로구창의문로5길24<NA>
49849861196823.3554630.8196823.3554630.8부암동-166종로구창의문로5나길4<NA>
49859862196858.5554667.0196858.5554667.0부암동-167종로구창의문로5나길9<NA>
49869863196874.2554611.1196874.2554611.1부암동-168종로구창의문로5나길18<NA>
49879864196993.0554744.7196993.0554744.7부암동-169종로구창의문로129-3<NA>
49889865196839.6554854.7196839.6554854.7부암동-170종로구창의문로10길31<NA>