Overview

Dataset statistics

Number of variables9
Number of observations103
Missing cells35
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory75.2 B

Variable types

Text5
Numeric2
DateTime1
Categorical1

Dataset

Description서울특별시 금천구 건축사사무소현황 정보로 사무소명 , 도로명주소, 지번주소, 위도, 경도, 전화번호, 대표자, 데이터기준일자 제공
Author서울특별시 금천구
URLhttps://www.data.go.kr/data/3081182/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
기타 유의사항 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
전화번호 has 35 (34.0%) missing valuesMissing
사무소명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:44:06.739989
Analysis finished2024-03-14 09:44:09.549879
Duration2.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사무소명
Text

UNIQUE 

Distinct103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size952.0 B
2024-03-14T18:44:10.245760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length12.038835
Min length7

Characters and Unicode

Total characters1240
Distinct characters166
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

Unique103 ?
Unique (%)100.0%

Sample

1st row(주)건축사사무소 이존
2nd row(주)건축사사무소동영아키텍
3rd row(주)공간기술단건축사사무소
4th row(주)금호이엔씨종합건축사사무소
5th row(주)길종합건축사사무소
ValueCountFrequency (%)
건축사사무소 34
 
21.5%
주식회사 14
 
8.9%
종합건축사사무소 3
 
1.9%
아키뱅크건축사사무소 1
 
0.6%
간향 1
 
0.6%
제이엔건축사사무소 1
 
0.6%
인자인건축사사무소 1
 
0.6%
유중엔지니어링 1
 
0.6%
우림종합건축사사무소 1
 
0.6%
우리이엔지건축사사무소 1
 
0.6%
Other values (100) 100
63.3%
2024-03-14T18:44:11.577717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 224
18.1%
건 108
 
8.7%
축 107
 
8.6%
무 103
 
8.3%
소 103
 
8.3%
56
 
4.5%
주 48
 
3.9%
( 31
 
2.5%
) 31
 
2.5%
이 23
 
1.9%
Other values (156) 406
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1107
89.3%
Space Separator 56
 
4.5%
Open Punctuation 31
 
2.5%
Close Punctuation 31
 
2.5%
Uppercase Letter 11
 
0.9%
Decimal Number 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 224
20.2%
건 108
 
9.8%
축 107
 
9.7%
무 103
 
9.3%
소 103
 
9.3%
주 48
 
4.3%
이 23
 
2.1%
종 20
 
1.8%
합 19
 
1.7%
식 17
 
1.5%
Other values (140) 335
30.3%
Uppercase Letter
ValueCountFrequency (%)
D 2
18.2%
A 2
18.2%
L 1
9.1%
P 1
9.1%
Y 1
9.1%
B 1
9.1%
I 1
9.1%
N 1
9.1%
E 1
9.1%
Decimal Number
ValueCountFrequency (%)
0 1
33.3%
1 1
33.3%
5 1
33.3%
Space Separator
ValueCountFrequency (%)
56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1107
89.3%
Common 122
 
9.8%
Latin 11
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 224
20.2%
건 108
 
9.8%
축 107
 
9.7%
무 103
 
9.3%
소 103
 
9.3%
주 48
 
4.3%
이 23
 
2.1%
종 20
 
1.8%
합 19
 
1.7%
식 17
 
1.5%
Other values (140) 335
30.3%
Latin
ValueCountFrequency (%)
D 2
18.2%
A 2
18.2%
L 1
9.1%
P 1
9.1%
Y 1
9.1%
B 1
9.1%
I 1
9.1%
N 1
9.1%
E 1
9.1%
Common
ValueCountFrequency (%)
56
45.9%
( 31
25.4%
) 31
25.4%
0 1
 
0.8%
1 1
 
0.8%
5 1
 
0.8%
. 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1107
89.3%
ASCII 133
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 224
20.2%
건 108
 
9.8%
축 107
 
9.7%
무 103
 
9.3%
소 103
 
9.3%
주 48
 
4.3%
이 23
 
2.1%
종 20
 
1.8%
합 19
 
1.7%
식 17
 
1.5%
Other values (140) 335
30.3%
ASCII
ValueCountFrequency (%)
56
42.1%
( 31
23.3%
) 31
23.3%
D 2
 
1.5%
A 2
 
1.5%
L 1
 
0.8%
0 1
 
0.8%
1 1
 
0.8%
5 1
 
0.8%
P 1
 
0.8%
Other values (6) 6
 
4.5%

도로명주소
Text

Distinct102
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size952.0 B
2024-03-14T18:44:12.599277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length37.300971
Min length18

Characters and Unicode

Total characters3842
Distinct characters154
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

Unique101 ?
Unique (%)98.1%

Sample

1st row서울특별시 금천구 가산디지털2로 173-0, 207호
2nd row서울특별시 금천구 가산디지털1로 168 C동 502호 (가산동)
3rd row서울특별시 금천구 디지털로9길 46-0, (가산동) 이앤씨드림타워 7차 1301, 1302호
4th row서울특별시 금천구 시흥대로71길 40 301호(시흥동, 금호빌딩) (시흥동)
5th row서울특별시 금천구 가산디지털2로 53-0, 한라시그마밸리 807호
ValueCountFrequency (%)
서울특별시 103
 
15.5%
금천구 103
 
15.5%
가산동 29
 
4.4%
가산디지털2로 20
 
3.0%
가산디지털1로 19
 
2.9%
시흥대로 11
 
1.7%
시흥동 10
 
1.5%
디지털로9길 8
 
1.2%
서부샛길 7
 
1.1%
606 6
 
0.9%
Other values (263) 347
52.3%
2024-03-14T18:44:14.153252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
599
 
15.6%
1 209
 
5.4%
0 151
 
3.9%
시 138
 
3.6%
산 111
 
2.9%
금 111
 
2.9%
서 110
 
2.9%
2 106
 
2.8%
천 104
 
2.7%
울 103
 
2.7%
Other values (144) 2100
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2105
54.8%
Decimal Number 824
 
21.4%
Space Separator 599
 
15.6%
Other Punctuation 89
 
2.3%
Dash Punctuation 66
 
1.7%
Close Punctuation 63
 
1.6%
Open Punctuation 63
 
1.6%
Uppercase Letter 23
 
0.6%
Lowercase Letter 10
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 138
 
6.6%
산 111
 
5.3%
금 111
 
5.3%
서 110
 
5.2%
천 104
 
4.9%
울 103
 
4.9%
구 103
 
4.9%
별 103
 
4.9%
특 103
 
4.9%
호 99
 
4.7%
Other values (105) 1020
48.5%
Uppercase Letter
ValueCountFrequency (%)
A 6
26.1%
B 4
17.4%
O 2
 
8.7%
K 2
 
8.7%
C 1
 
4.3%
M 1
 
4.3%
S 1
 
4.3%
V 1
 
4.3%
T 1
 
4.3%
W 1
 
4.3%
Other values (3) 3
13.0%
Decimal Number
ValueCountFrequency (%)
1 209
25.4%
0 151
18.3%
2 106
12.9%
3 70
 
8.5%
6 63
 
7.6%
5 56
 
6.8%
4 50
 
6.1%
7 47
 
5.7%
9 43
 
5.2%
8 29
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
k 2
20.0%
c 2
20.0%
r 1
10.0%
e 1
10.0%
m 1
10.0%
t 1
10.0%
o 1
10.0%
w 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 85
95.5%
. 4
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 62
98.4%
] 1
 
1.6%
Open Punctuation
ValueCountFrequency (%)
( 62
98.4%
[ 1
 
1.6%
Space Separator
ValueCountFrequency (%)
599
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2105
54.8%
Common 1704
44.4%
Latin 33
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 138
 
6.6%
산 111
 
5.3%
금 111
 
5.3%
서 110
 
5.2%
천 104
 
4.9%
울 103
 
4.9%
구 103
 
4.9%
별 103
 
4.9%
특 103
 
4.9%
호 99
 
4.7%
Other values (105) 1020
48.5%
Latin
ValueCountFrequency (%)
A 6
18.2%
B 4
 
12.1%
k 2
 
6.1%
O 2
 
6.1%
c 2
 
6.1%
K 2
 
6.1%
C 1
 
3.0%
M 1
 
3.0%
r 1
 
3.0%
S 1
 
3.0%
Other values (11) 11
33.3%
Common
ValueCountFrequency (%)
599
35.2%
1 209
 
12.3%
0 151
 
8.9%
2 106
 
6.2%
, 85
 
5.0%
3 70
 
4.1%
- 66
 
3.9%
6 63
 
3.7%
) 62
 
3.6%
( 62
 
3.6%
Other values (8) 231
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2105
54.8%
ASCII 1737
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
599
34.5%
1 209
 
12.0%
0 151
 
8.7%
2 106
 
6.1%
, 85
 
4.9%
3 70
 
4.0%
- 66
 
3.8%
6 63
 
3.6%
) 62
 
3.6%
( 62
 
3.6%
Other values (29) 264
15.2%
Hangul
ValueCountFrequency (%)
시 138
 
6.6%
산 111
 
5.3%
금 111
 
5.3%
서 110
 
5.2%
천 104
 
4.9%
울 103
 
4.9%
구 103
 
4.9%
별 103
 
4.9%
특 103
 
4.9%
호 99
 
4.7%
Other values (105) 1020
48.5%

지번주소
Text

Distinct96
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size952.0 B
2024-03-14T18:44:15.345450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length28.533981
Min length14

Characters and Unicode

Total characters2939
Distinct characters120
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

Unique92 ?
Unique (%)89.3%

Sample

1st row서울특별시 금천구 가산동 459-23, 207호
2nd row서울특별시 금천구 가산동 371-28, c동 502호
3rd row서울특별시 금천구 가산동 60-44 앤씨드림타워 7차 1301, 1302호
4th row서울특별시 금천구 시흥동 103-6, 301호
5th row서울특별시 금천구 가산동 대지 345-90 한라시그마밸리 807호
ValueCountFrequency (%)
금천구 101
18.1%
서울특별시 79
 
14.2%
가산동 69
 
12.4%
서울 24
 
4.3%
시흥동 21
 
3.8%
독산동 15
 
2.7%
대지 9
 
1.6%
543-1 8
 
1.4%
291-1 5
 
0.9%
991 4
 
0.7%
Other values (185) 222
39.9%
2024-03-14T18:44:17.070399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
462
 
15.7%
1 163
 
5.5%
동 130
 
4.4%
시 106
 
3.6%
서 103
 
3.5%
울 103
 
3.5%
산 103
 
3.5%
금 102
 
3.5%
천 102
 
3.5%
구 101
 
3.4%
Other values (110) 1464
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1507
51.3%
Decimal Number 748
25.5%
Space Separator 462
 
15.7%
Dash Punctuation 100
 
3.4%
Other Punctuation 54
 
1.8%
Uppercase Letter 26
 
0.9%
Close Punctuation 19
 
0.6%
Open Punctuation 19
 
0.6%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 130
 
8.6%
시 106
 
7.0%
서 103
 
6.8%
울 103
 
6.8%
산 103
 
6.8%
금 102
 
6.8%
천 102
 
6.8%
구 101
 
6.7%
가 83
 
5.5%
특 79
 
5.2%
Other values (83) 495
32.8%
Decimal Number
ValueCountFrequency (%)
1 163
21.8%
0 98
13.1%
5 85
11.4%
2 81
10.8%
3 79
10.6%
4 69
9.2%
9 69
9.2%
6 42
 
5.6%
7 32
 
4.3%
8 30
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
W 3
11.5%
O 3
11.5%
E 3
11.5%
T 3
11.5%
K 3
11.5%
R 3
11.5%
M 3
11.5%
A 3
11.5%
B 2
7.7%
Other Punctuation
ValueCountFrequency (%)
, 48
88.9%
. 6
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
c 3
75.0%
k 1
 
25.0%
Space Separator
ValueCountFrequency (%)
462
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1507
51.3%
Common 1402
47.7%
Latin 30
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 130
 
8.6%
시 106
 
7.0%
서 103
 
6.8%
울 103
 
6.8%
산 103
 
6.8%
금 102
 
6.8%
천 102
 
6.8%
구 101
 
6.7%
가 83
 
5.5%
특 79
 
5.2%
Other values (83) 495
32.8%
Common
ValueCountFrequency (%)
462
33.0%
1 163
 
11.6%
- 100
 
7.1%
0 98
 
7.0%
5 85
 
6.1%
2 81
 
5.8%
3 79
 
5.6%
4 69
 
4.9%
9 69
 
4.9%
, 48
 
3.4%
Other values (6) 148
 
10.6%
Latin
ValueCountFrequency (%)
W 3
10.0%
O 3
10.0%
E 3
10.0%
T 3
10.0%
K 3
10.0%
R 3
10.0%
M 3
10.0%
A 3
10.0%
c 3
10.0%
B 2
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1507
51.3%
ASCII 1432
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
462
32.3%
1 163
 
11.4%
- 100
 
7.0%
0 98
 
6.8%
5 85
 
5.9%
2 81
 
5.7%
3 79
 
5.5%
4 69
 
4.8%
9 69
 
4.8%
, 48
 
3.4%
Other values (17) 178
 
12.4%
Hangul
ValueCountFrequency (%)
동 130
 
8.6%
시 106
 
7.0%
서 103
 
6.8%
울 103
 
6.8%
산 103
 
6.8%
금 102
 
6.8%
천 102
 
6.8%
구 101
 
6.7%
가 83
 
5.5%
특 79
 
5.2%
Other values (83) 495
32.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct86
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.471072
Minimum37.443295
Maximum37.48602
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-14T18:44:17.485646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.443295
5-th percentile37.450762
Q137.465262
median37.474533
Q337.47983
95-th percentile37.484595
Maximum37.48602
Range0.042725
Interquartile range (IQR)0.014568365

Descriptive statistics

Standard deviation0.011291589
Coefficient of variation (CV)0.0003013415
Kurtosis-0.61864961
Mean37.471072
Median Absolute Deviation (MAD)0.00654325
Skewness-0.74025091
Sum3859.5204
Variance0.00012749998
MonotonicityNot monotonic
2024-03-14T18:44:17.926732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.48304345 4
 
3.9%
37.469281 4
 
3.9%
37.47995349 3
 
2.9%
37.456445 3
 
2.9%
37.485561 2
 
1.9%
37.479721 2
 
1.9%
37.4724347 2
 
1.9%
37.474564 2
 
1.9%
37.4722915 2
 
1.9%
37.448394 2
 
1.9%
Other values (76) 77
74.8%
ValueCountFrequency (%)
37.443295 1
1.0%
37.44818568 1
1.0%
37.448394 2
1.9%
37.450371 1
1.0%
37.450754 1
1.0%
37.450831 1
1.0%
37.45112 1
1.0%
37.451132 1
1.0%
37.45114 1
1.0%
37.45122 1
1.0%
ValueCountFrequency (%)
37.48602 1
 
1.0%
37.485561 2
1.9%
37.48543 1
 
1.0%
37.484834 1
 
1.0%
37.484649 1
 
1.0%
37.484105 1
 
1.0%
37.4832 1
 
1.0%
37.483085 1
 
1.0%
37.483079 1
 
1.0%
37.48304345 4
3.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct86
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.88838
Minimum126.87652
Maximum126.91443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-14T18:44:18.543582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.87652
5-th percentile126.87701
Q1126.88097
median126.88642
Q3126.89744
95-th percentile126.90349
Maximum126.91443
Range0.0379069
Interquartile range (IQR)0.0164671

Descriptive statistics

Standard deviation0.009163218
Coefficient of variation (CV)7.2214791 × 10-5
Kurtosis-0.66988405
Mean126.88838
Median Absolute Deviation (MAD)0.0077553
Skewness0.55459653
Sum13069.503
Variance8.3964565 × 10-5
MonotonicityNot monotonic
2024-03-14T18:44:19.010960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8765231 4
 
3.9%
126.895202 4
 
3.9%
126.8770082 3
 
2.9%
126.898038 3
 
2.9%
126.879956 2
 
1.9%
126.8815446 2
 
1.9%
126.889455 2
 
1.9%
126.8816805 2
 
1.9%
126.88612 2
 
1.9%
126.903547 2
 
1.9%
Other values (76) 77
74.8%
ValueCountFrequency (%)
126.8765231 4
3.9%
126.876749 1
 
1.0%
126.8770082 3
2.9%
126.877016 1
 
1.0%
126.87711 1
 
1.0%
126.877251 1
 
1.0%
126.87732 1
 
1.0%
126.8774639 1
 
1.0%
126.87814 1
 
1.0%
126.87834 1
 
1.0%
ValueCountFrequency (%)
126.91443 1
1.0%
126.910614 1
1.0%
126.904109 1
1.0%
126.903547 2
1.9%
126.9035364 1
1.0%
126.903051 1
1.0%
126.90151 1
1.0%
126.9015 1
1.0%
126.90144 1
1.0%
126.901355 1
1.0%

전화번호
Text

MISSING 

Distinct67
Distinct (%)98.5%
Missing35
Missing (%)34.0%
Memory size952.0 B
2024-03-14T18:44:19.983342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.470588
Min length11

Characters and Unicode

Total characters780
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)97.1%

Sample

1st row070-4226-4011
2nd row02-544-3302
3rd row02-586-3634
4th row02-808-0400
5th row02-782-5980
ValueCountFrequency (%)
02-897-6569 2
 
2.9%
070-4226-4011 1
 
1.5%
02-894-2300 1
 
1.5%
02-6951-2162 1
 
1.5%
02-818-9151 1
 
1.5%
02-2648-6963 1
 
1.5%
02-523-6831 1
 
1.5%
02-891-8422 1
 
1.5%
02-6112-1510 1
 
1.5%
02-3462-1336 1
 
1.5%
Other values (57) 57
83.8%
2024-03-14T18:44:21.380155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 136
17.4%
2 133
17.1%
0 129
16.5%
6 66
8.5%
3 54
 
6.9%
1 53
 
6.8%
8 50
 
6.4%
5 48
 
6.2%
4 44
 
5.6%
7 36
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 644
82.6%
Dash Punctuation 136
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 133
20.7%
0 129
20.0%
6 66
10.2%
3 54
8.4%
1 53
 
8.2%
8 50
 
7.8%
5 48
 
7.5%
4 44
 
6.8%
7 36
 
5.6%
9 31
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 780
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 136
17.4%
2 133
17.1%
0 129
16.5%
6 66
8.5%
3 54
 
6.9%
1 53
 
6.8%
8 50
 
6.4%
5 48
 
6.2%
4 44
 
5.6%
7 36
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 136
17.4%
2 133
17.1%
0 129
16.5%
6 66
8.5%
3 54
 
6.9%
1 53
 
6.8%
8 50
 
6.4%
5 48
 
6.2%
4 44
 
5.6%
7 36
 
4.6%

대표자
Text

Distinct100
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size952.0 B
2024-03-14T18:44:22.652406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.2718447
Min length2

Characters and Unicode

Total characters337
Distinct characters115
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

Unique97 ?
Unique (%)94.2%

Sample

1st row이평주
2nd row박길영
3rd row정찬형
4th row박금호
5th row이길수
ValueCountFrequency (%)
김란수 2
 
1.8%
이상철 2
 
1.8%
김동현 2
 
1.8%
정봉섭 1
 
0.9%
오태영 1
 
0.9%
김정범 1
 
0.9%
김지남 1
 
0.9%
최정화 1
 
0.9%
안희창 1
 
0.9%
백병률 1
 
0.9%
Other values (96) 96
88.1%
2024-03-14T18:44:24.344721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 27
 
8.0%
이 22
 
6.5%
정 14
 
4.2%
호 11
 
3.3%
현 10
 
3.0%
진 10
 
3.0%
수 9
 
2.7%
상 7
 
2.1%
영 7
 
2.1%
동 6
 
1.8%
Other values (105) 214
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
96.7%
Space Separator 6
 
1.8%
Other Punctuation 5
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 27
 
8.3%
이 22
 
6.7%
정 14
 
4.3%
호 11
 
3.4%
현 10
 
3.1%
진 10
 
3.1%
수 9
 
2.8%
상 7
 
2.1%
영 7
 
2.1%
동 6
 
1.8%
Other values (103) 203
62.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
96.7%
Common 11
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 27
 
8.3%
이 22
 
6.7%
정 14
 
4.3%
호 11
 
3.4%
현 10
 
3.1%
진 10
 
3.1%
수 9
 
2.8%
상 7
 
2.1%
영 7
 
2.1%
동 6
 
1.8%
Other values (103) 203
62.3%
Common
ValueCountFrequency (%)
6
54.5%
, 5
45.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 326
96.7%
ASCII 11
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 27
 
8.3%
이 22
 
6.7%
정 14
 
4.3%
호 11
 
3.4%
현 10
 
3.1%
진 10
 
3.1%
수 9
 
2.8%
상 7
 
2.1%
영 7
 
2.1%
동 6
 
1.8%
Other values (103) 203
62.3%
ASCII
ValueCountFrequency (%)
6
54.5%
, 5
45.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size952.0 B
Minimum2023-05-09 00:00:00
Maximum2023-05-09 00:00:00
2024-03-14T18:44:24.536472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:44:24.781550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

기타 유의사항
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size952.0 B
<NA>
68 
전화번호 항목 데이터 미수집
35 

Length

Max length15
Median length4
Mean length7.7378641
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 68
66.0%
전화번호 항목 데이터 미수집 35
34.0%

Length

2024-03-14T18:44:25.042671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:44:25.293326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
32.7%
전화번호 35
16.8%
항목 35
16.8%
데이터 35
16.8%
미수집 35
16.8%

Interactions

2024-03-14T18:44:08.383486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:44:07.918966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:44:08.530343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:44:08.142076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:44:25.491543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지번주소위도경도전화번호대표자
지번주소1.0001.0001.0001.0000.981
위도1.0001.0000.8900.9530.916
경도1.0000.8901.0000.9690.945
전화번호1.0000.9530.9691.0001.000
대표자0.9810.9160.9451.0001.000
2024-03-14T18:44:25.757039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도기타 유의사항
위도1.000-0.8681.000
경도-0.8681.0001.000
기타 유의사항1.0001.0001.000

Missing values

2024-03-14T18:44:08.928307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:44:09.377396image/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

사무소명도로명주소지번주소위도경도전화번호대표자데이터기준일자기타 유의사항
0(주)건축사사무소 이존서울특별시 금천구 가산디지털2로 173-0, 207호서울특별시 금천구 가산동 459-23, 207호37.483085126.877251070-4226-4011이평주2023-05-09<NA>
1(주)건축사사무소동영아키텍서울특별시 금천구 가산디지털1로 168 C동 502호 (가산동)서울특별시 금천구 가산동 371-28, c동 502호37.47987126.8824502-544-3302박길영2023-05-09<NA>
2(주)공간기술단건축사사무소서울특별시 금천구 디지털로9길 46-0, (가산동) 이앤씨드림타워 7차 1301, 1302호서울특별시 금천구 가산동 60-44 앤씨드림타워 7차 1301, 1302호37.465285126.89817102-586-3634정찬형2023-05-09<NA>
3(주)금호이엔씨종합건축사사무소서울특별시 금천구 시흥대로71길 40 301호(시흥동, 금호빌딩) (시흥동)서울특별시 금천구 시흥동 103-6, 301호37.45539126.8993402-808-0400박금호2023-05-09<NA>
4(주)길종합건축사사무소서울특별시 금천구 가산디지털2로 53-0, 한라시그마밸리 807호서울특별시 금천구 가산동 대지 345-90 한라시그마밸리 807호37.479907126.87701602-782-5980이길수2023-05-09<NA>
5(주)다빈건축사사무소서울특별시 금천구 시흥대로 193 아람아이씨티타워 1013호,1014호 (시흥동)서울특별시 금천구 시흥동 991 1013호, 1014호37.45114126.9015102-6267-3678김정훈2023-05-09<NA>
6(주)라움엔지니어링종합건축사사무소서울특별시 금천구 디지털로9길 32-0, 갑을그레이트밸리 A-505호서울특별시 금천구 가산동 대지 60-5 갑을그레이트밸리 A-505호37.481205126.88635902-3397-7275김동완2023-05-09<NA>
7(주)레드원건축사사무소서울특별시 금천구 가산로9길 66 302호(가산동, 더리즌밸리) (가산동)서울특별시 가산동 60-46 302호37.47613126.8883502-6275-6300임원혁2023-05-09<NA>
8(주)바다종합건축사사무소서울특별시 금천구 시흥대로73길 67-0, 12층1203호(시흥동,엠메디컬타워)서울특별시 금천구 시흥동 1031,1203호37.471114126.88383402-854-9772서필호2023-05-09<NA>
9(주)산다건축사사무소서울특별시 금천구 시흥대로 352 삼미뉴타워 202호 (독산동)서울특별시 독산동 1031-27, 삼미뉴타워 202호37.46494126.8979202-896-4224김무경2023-05-09<NA>
사무소명도로명주소지번주소위도경도전화번호대표자데이터기준일자기타 유의사항
93지우건축사사무소서울특별시 금천구 디지털로9길 32 갑을그레이트밸리 B동 505-1호 (가산동)서울특별시 금천구 가산동 60-5 갑을그레이트밸리 B동 505-1호37.47952126.8874702-2627-3900오영섭2023-05-09<NA>
94터인스 건축사사무소서울특별시 금천구 가산디지털1로 84 409-8호 (가산동, 에이스하이앤드타워8차) (가산동)서울특별시 금천구 가산동 345-4 409-8호 (에이스하이앤드타워8차)37.473525126.885547<NA>김진선2023-05-09전화번호 항목 데이터 미수집
95텐건축사사무소서울특별시 금천구 시흥대로73길 67 금천엠타워 1115호 (시흥동)서울특별시 금천구 시흥동 1031 1115호(금천엠타워)37.450831126.91061402-804-8346차주영2023-05-09<NA>
96팔건축사사무소 주식회사서울특별시 금천구 시흥대로50길 12-11 3층 (시흥동)서울특별시 금천구 시흥동 902, 3층37.450754126.90305102-6332-0318홍다솔, 이진경2023-05-09<NA>
97하다건축사사무소서울특별시 금천구 가산디지털2로 14-0, 1114호 (가산동, 대륭테크노타운12차)서울특별시 금천구 가산동 대지 327-32 대륭테크노타운12차 1114호37.477392126.883609<NA>이승호2023-05-09전화번호 항목 데이터 미수집
98현 건축사사무소서울특별시 금천구 가산디지털1로 25 대륭테크노타운 17차 1303호 (가산동)서울특별시 금천구 가산동 670 1303호37.4683126.88612<NA>김현하2023-05-09전화번호 항목 데이터 미수집
99혜안도시건축 건축사사무소서울특별시 금천구 디지털로 173-0, 1103,1104호(가산동, 엘리시아)서울특별시 금천구 가산동 60-69, 1103,1104호(가산동, 엘리시아)37.484834126.883802-866-2928조석현2023-05-09<NA>
100화이트그라운드 건축사사무소서울특별시 금천구 가산디지털1로 225 에이스가산포휴 210호 (가산동)서울특별시 금천구 가산동 517-4 에이스가산포휴 210호37.48543126.87871<NA>방용민2023-05-09전화번호 항목 데이터 미수집
101희성건축사사무소서울특별시 금천구 가산디지털1로 142-0, 1110호서울특별시 금천구 가산동 371-57, 1110호37.478454126.883308<NA>권호석2023-05-09전화번호 항목 데이터 미수집
102희훈건축사사무소서울특별시 금천구 시흥대로73길 11-0, 2층 209호서울특별시 금천구 시흥동 109-1 , 2층 209호37.477215126.88226602-802-2827최병훈2023-05-09<NA>