Overview

Dataset statistics

Number of variables9
Number of observations56
Missing cells48
Missing cells (%)9.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory76.3 B

Variable types

Categorical2
Text4
Numeric2
DateTime1

Dataset

Description경기도 성남시 지식산업센터현황(구분,지식산업센터명,위치,연락처,건축연면적,준공연도,입주업체수 등)입니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/3073725/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일 has constant value ""Constant
건축연면적(제곱미터) is highly overall correlated with 입주업체수High correlation
입주업체수 is highly overall correlated with 건축연면적(제곱미터)High correlation
용도지역 is highly imbalanced (51.9%)Imbalance
소재지도로명주소 has 2 (3.6%) missing valuesMissing
비고 has 46 (82.1%) missing valuesMissing
지식산업센터명칭 has unique valuesUnique
소재지지번주소 has unique valuesUnique
건축연면적(제곱미터) has unique valuesUnique
입주업체수 has 6 (10.7%) zerosZeros

Reproduction

Analysis started2024-03-14 11:27:11.620862
Analysis finished2024-03-14 11:27:14.149991
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size576.0 B
성남시
56 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 56
100.0%

Length

2024-03-14T20:27:14.352448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:27:14.643608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시 56
100.0%

지식산업센터명칭
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
2024-03-14T20:27:15.505647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length8.1785714
Min length3

Characters and Unicode

Total characters458
Distinct characters122
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

Unique56 ?
Unique (%)100.0%

Sample

1st row분당테크노파크
2nd row남서울첨단
3rd row반도아이비밸리
4th row현대지식산업센터
5th rowLH기업성장센터
ValueCountFrequency (%)
2차 5
 
6.6%
중앙인더스피아 4
 
5.3%
우림라이온스밸리 4
 
5.3%
3차 3
 
3.9%
5차 2
 
2.6%
쌍용it트윈타워 2
 
2.6%
중일아인스프라츠 2
 
2.6%
센트럴 2
 
2.6%
비즈타워 2
 
2.6%
성남 2
 
2.6%
Other values (46) 48
63.2%
2024-03-14T20:27:16.840463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
4.4%
크 16
 
3.5%
차 16
 
3.5%
스 16
 
3.5%
센 15
 
3.3%
테 13
 
2.8%
노 13
 
2.8%
터 13
 
2.8%
이 13
 
2.8%
타 12
 
2.6%
Other values (112) 311
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 377
82.3%
Uppercase Letter 30
 
6.6%
Space Separator 20
 
4.4%
Decimal Number 20
 
4.4%
Close Punctuation 4
 
0.9%
Open Punctuation 4
 
0.9%
Lowercase Letter 2
 
0.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
크 16
 
4.2%
차 16
 
4.2%
스 16
 
4.2%
센 15
 
4.0%
테 13
 
3.4%
노 13
 
3.4%
터 13
 
3.4%
이 13
 
3.4%
타 12
 
3.2%
리 12
 
3.2%
Other values (89) 238
63.1%
Uppercase Letter
ValueCountFrequency (%)
I 6
20.0%
T 4
13.3%
S 4
13.3%
K 3
10.0%
G 2
 
6.7%
L 2
 
6.7%
B 2
 
6.7%
H 2
 
6.7%
V 1
 
3.3%
C 1
 
3.3%
Other values (3) 3
10.0%
Decimal Number
ValueCountFrequency (%)
2 8
40.0%
1 5
25.0%
3 4
20.0%
5 3
 
15.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
50.0%
z 1
50.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 377
82.3%
Common 49
 
10.7%
Latin 32
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
크 16
 
4.2%
차 16
 
4.2%
스 16
 
4.2%
센 15
 
4.0%
테 13
 
3.4%
노 13
 
3.4%
터 13
 
3.4%
이 13
 
3.4%
타 12
 
3.2%
리 12
 
3.2%
Other values (89) 238
63.1%
Latin
ValueCountFrequency (%)
I 6
18.8%
T 4
12.5%
S 4
12.5%
K 3
9.4%
G 2
 
6.2%
L 2
 
6.2%
B 2
 
6.2%
H 2
 
6.2%
V 1
 
3.1%
i 1
 
3.1%
Other values (5) 5
15.6%
Common
ValueCountFrequency (%)
20
40.8%
2 8
 
16.3%
1 5
 
10.2%
3 4
 
8.2%
) 4
 
8.2%
( 4
 
8.2%
5 3
 
6.1%
- 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 377
82.3%
ASCII 81
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
24.7%
2 8
 
9.9%
I 6
 
7.4%
1 5
 
6.2%
T 4
 
4.9%
3 4
 
4.9%
) 4
 
4.9%
( 4
 
4.9%
S 4
 
4.9%
5 3
 
3.7%
Other values (13) 19
23.5%
Hangul
ValueCountFrequency (%)
크 16
 
4.2%
차 16
 
4.2%
스 16
 
4.2%
센 15
 
4.0%
테 13
 
3.4%
노 13
 
3.4%
터 13
 
3.4%
이 13
 
3.4%
타 12
 
3.2%
리 12
 
3.2%
Other values (89) 238
63.1%

소재지지번주소
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
2024-03-14T20:27:17.789636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length21.571429
Min length14

Characters and Unicode

Total characters1208
Distinct characters55
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

Unique56 ?
Unique (%)100.0%

Sample

1st row경기도 성남시 분당구 야탑동 145
2nd row경기도 성남시 분당구 백현동 404-1
3rd row경기도 성남시 수정구 고등동 603
4th row경기도 성남시 수정구 고등동 572
5th row경기도 성남시 수정구 시흥동 294-2
ValueCountFrequency (%)
경기도 53
19.6%
성남시 53
19.6%
중원구 44
16.2%
상대원동 41
15.1%
수정구 7
 
2.6%
시흥동 4
 
1.5%
판교제2테크노밸리 3
 
1.1%
분당구 2
 
0.7%
고등동 2
 
0.7%
138-6 1
 
0.4%
Other values (61) 61
22.5%
2024-03-14T20:27:19.154939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
17.8%
원 88
 
7.3%
시 57
 
4.7%
구 54
 
4.5%
경 53
 
4.4%
기 53
 
4.4%
동 53
 
4.4%
남 53
 
4.4%
성 53
 
4.4%
도 53
 
4.4%
Other values (45) 476
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 714
59.1%
Decimal Number 227
 
18.8%
Space Separator 215
 
17.8%
Dash Punctuation 46
 
3.8%
Uppercase Letter 3
 
0.2%
Open Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 88
12.3%
시 57
 
8.0%
구 54
 
7.6%
경 53
 
7.4%
기 53
 
7.4%
동 53
 
7.4%
남 53
 
7.4%
성 53
 
7.4%
도 53
 
7.4%
대 44
 
6.2%
Other values (29) 153
21.4%
Decimal Number
ValueCountFrequency (%)
1 49
21.6%
3 41
18.1%
2 38
16.7%
4 34
15.0%
5 25
11.0%
6 10
 
4.4%
7 9
 
4.0%
0 8
 
3.5%
8 7
 
3.1%
9 6
 
2.6%
Space Separator
ValueCountFrequency (%)
215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 714
59.1%
Common 491
40.6%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 88
12.3%
시 57
 
8.0%
구 54
 
7.6%
경 53
 
7.4%
기 53
 
7.4%
동 53
 
7.4%
남 53
 
7.4%
성 53
 
7.4%
도 53
 
7.4%
대 44
 
6.2%
Other values (29) 153
21.4%
Common
ValueCountFrequency (%)
215
43.8%
1 49
 
10.0%
- 46
 
9.4%
3 41
 
8.4%
2 38
 
7.7%
4 34
 
6.9%
5 25
 
5.1%
6 10
 
2.0%
7 9
 
1.8%
0 8
 
1.6%
Other values (5) 16
 
3.3%
Latin
ValueCountFrequency (%)
E 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 714
59.1%
ASCII 494
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
43.5%
1 49
 
9.9%
- 46
 
9.3%
3 41
 
8.3%
2 38
 
7.7%
4 34
 
6.9%
5 25
 
5.1%
6 10
 
2.0%
7 9
 
1.8%
0 8
 
1.6%
Other values (6) 19
 
3.8%
Hangul
ValueCountFrequency (%)
원 88
12.3%
시 57
 
8.0%
구 54
 
7.6%
경 53
 
7.4%
기 53
 
7.4%
동 53
 
7.4%
남 53
 
7.4%
성 53
 
7.4%
도 53
 
7.4%
대 44
 
6.2%
Other values (29) 153
21.4%

소재지도로명주소
Text

MISSING 

Distinct54
Distinct (%)100.0%
Missing2
Missing (%)3.6%
Memory size576.0 B
2024-03-14T20:27:20.111863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length20.814815
Min length14

Characters and Unicode

Total characters1124
Distinct characters61
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)100.0%

Sample

1st row경기도 성남시 분당구 판교로 697
2nd row경기도 성남시 분당구 대왕판교로 395번길8
3rd row경기도 성남시 수정구 청계산로 686
4th row경기도 성남시 수정구 고등로 3
5th row경기도 성남시 수정구 창업로 54
ValueCountFrequency (%)
경기도 53
19.8%
성남시 53
19.8%
중원구 43
16.0%
둔촌대로 13
 
4.9%
사기막골로 11
 
4.1%
수정구 8
 
3.0%
갈마치로 8
 
3.0%
14 2
 
0.7%
사기막골로62번길 2
 
0.7%
순환로 2
 
0.7%
Other values (66) 73
27.2%
2024-03-14T20:27:21.470037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
214
19.0%
기 69
 
6.1%
경 53
 
4.7%
시 53
 
4.7%
구 53
 
4.7%
로 53
 
4.7%
남 53
 
4.7%
성 53
 
4.7%
도 53
 
4.7%
원 43
 
3.8%
Other values (51) 427
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 733
65.2%
Space Separator 214
 
19.0%
Decimal Number 175
 
15.6%
Dash Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 69
 
9.4%
경 53
 
7.2%
시 53
 
7.2%
구 53
 
7.2%
로 53
 
7.2%
남 53
 
7.2%
성 53
 
7.2%
도 53
 
7.2%
원 43
 
5.9%
중 43
 
5.9%
Other values (38) 207
28.2%
Decimal Number
ValueCountFrequency (%)
4 29
16.6%
1 28
16.0%
5 22
12.6%
2 20
11.4%
8 15
8.6%
3 15
8.6%
0 13
7.4%
6 13
7.4%
7 11
 
6.3%
9 9
 
5.1%
Space Separator
ValueCountFrequency (%)
214
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 733
65.2%
Common 390
34.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 69
 
9.4%
경 53
 
7.2%
시 53
 
7.2%
구 53
 
7.2%
로 53
 
7.2%
남 53
 
7.2%
성 53
 
7.2%
도 53
 
7.2%
원 43
 
5.9%
중 43
 
5.9%
Other values (38) 207
28.2%
Common
ValueCountFrequency (%)
214
54.9%
4 29
 
7.4%
1 28
 
7.2%
5 22
 
5.6%
2 20
 
5.1%
8 15
 
3.8%
3 15
 
3.8%
0 13
 
3.3%
6 13
 
3.3%
7 11
 
2.8%
Other values (2) 10
 
2.6%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 733
65.2%
ASCII 391
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
214
54.7%
4 29
 
7.4%
1 28
 
7.2%
5 22
 
5.6%
2 20
 
5.1%
8 15
 
3.8%
3 15
 
3.8%
0 13
 
3.3%
6 13
 
3.3%
7 11
 
2.8%
Other values (3) 11
 
2.8%
Hangul
ValueCountFrequency (%)
기 69
 
9.4%
경 53
 
7.2%
시 53
 
7.2%
구 53
 
7.2%
로 53
 
7.2%
남 53
 
7.2%
성 53
 
7.2%
도 53
 
7.2%
원 43
 
5.9%
중 43
 
5.9%
Other values (38) 207
28.2%

용도지역
Categorical

IMBALANCE 

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size576.0 B
일반공업
43 
준공업지역
6 
준주거지역
 
3
근린상업
 
2
자연녹지
 
1

Length

Max length10
Median length4
Mean length4.2678571
Min length4

Unique

Unique2 ?
Unique (%)3.6%

Sample

1st row근린상업
2nd row자연녹지
3rd row근린상업
4th row준주거지역
5th row준공업지역

Common Values

ValueCountFrequency (%)
일반공업 43
76.8%
준공업지역 6
 
10.7%
준주거지역 3
 
5.4%
근린상업 2
 
3.6%
자연녹지 1
 
1.8%
복합용지+준주거지역 1
 
1.8%

Length

2024-03-14T20:27:21.897890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:27:22.235869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반공업 43
76.8%
준공업지역 6
 
10.7%
준주거지역 3
 
5.4%
근린상업 2
 
3.6%
자연녹지 1
 
1.8%
복합용지+준주거지역 1
 
1.8%

건축연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51416.875
Minimum3361
Maximum196562
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size632.0 B
2024-03-14T20:27:22.618836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3361
5-th percentile9013.25
Q124802.25
median41461.5
Q362514.75
95-th percentile109701.5
Maximum196562
Range193201
Interquartile range (IQR)37712.5

Descriptive statistics

Standard deviation39710.177
Coefficient of variation (CV)0.77231798
Kurtosis4.7185148
Mean51416.875
Median Absolute Deviation (MAD)19760
Skewness1.9017462
Sum2879345
Variance1.5768982 × 109
MonotonicityNot monotonic
2024-03-14T20:27:23.082311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193217 1
 
1.8%
19392 1
 
1.8%
196562 1
 
1.8%
65136 1
 
1.8%
99283 1
 
1.8%
16461 1
 
1.8%
37582 1
 
1.8%
20383 1
 
1.8%
14848 1
 
1.8%
19580 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
3361 1
1.8%
6501 1
1.8%
8120 1
1.8%
9311 1
1.8%
9697 1
1.8%
10496 1
1.8%
14848 1
1.8%
16461 1
1.8%
18621 1
1.8%
19392 1
1.8%
ValueCountFrequency (%)
196562 1
1.8%
193217 1
1.8%
140396 1
1.8%
99470 1
1.8%
99283 1
1.8%
97706 1
1.8%
95588 1
1.8%
94465 1
1.8%
83481 1
1.8%
74715 1
1.8%

입주업체수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.285714
Minimum0
Maximum424
Zeros6
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size632.0 B
2024-03-14T20:27:23.508732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median48
Q3103.25
95-th percentile224
Maximum424
Range424
Interquartile range (IQR)91.25

Descriptive statistics

Standard deviation78.433229
Coefficient of variation (CV)1.1486038
Kurtosis7.0202704
Mean68.285714
Median Absolute Deviation (MAD)41.5
Skewness2.2261767
Sum3824
Variance6151.7714
MonotonicityNot monotonic
2024-03-14T20:27:23.926232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 6
 
10.7%
13 3
 
5.4%
48 2
 
3.6%
12 2
 
3.6%
3 2
 
3.6%
57 2
 
3.6%
138 1
 
1.8%
245 1
 
1.8%
114 1
 
1.8%
112 1
 
1.8%
Other values (35) 35
62.5%
ValueCountFrequency (%)
0 6
10.7%
1 1
 
1.8%
2 1
 
1.8%
3 2
 
3.6%
4 1
 
1.8%
6 1
 
1.8%
10 1
 
1.8%
12 2
 
3.6%
13 3
5.4%
18 1
 
1.8%
ValueCountFrequency (%)
424 1
1.8%
248 1
1.8%
245 1
1.8%
217 1
1.8%
160 1
1.8%
143 1
1.8%
139 1
1.8%
138 1
1.8%
120 1
1.8%
117 1
1.8%

비고
Text

MISSING 

Distinct7
Distinct (%)70.0%
Missing46
Missing (%)82.1%
Memory size576.0 B
2024-03-14T20:27:24.552378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length9.3
Min length4

Characters and Unicode

Total characters93
Distinct characters31
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

Unique6 ?
Unique (%)60.0%

Sample

1st row공장등록업체수
2nd row공장등록업체수
3rd row공장등록업체수
4th row공장등록업체수
5th row2026. 12. 준공예정
ValueCountFrequency (%)
공장등록업체수 4
19.0%
12 2
 
9.5%
준공 2
 
9.5%
예정 2
 
9.5%
2026 1
 
4.8%
준공예정 1
 
4.8%
임시승인 1
 
4.8%
입주자 1
 
4.8%
모집 1
 
4.8%
미공고 1
 
4.8%
Other values (5) 5
23.8%
2024-03-14T20:27:25.556223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
11.8%
공 8
 
8.6%
2 8
 
8.6%
. 6
 
6.5%
수 4
 
4.3%
장 4
 
4.3%
정 4
 
4.3%
체 4
 
4.3%
업 4
 
4.3%
록 4
 
4.3%
Other values (21) 36
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59
63.4%
Decimal Number 17
 
18.3%
Space Separator 11
 
11.8%
Other Punctuation 6
 
6.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 8
13.6%
수 4
 
6.8%
장 4
 
6.8%
정 4
 
6.8%
체 4
 
6.8%
업 4
 
6.8%
록 4
 
6.8%
등 4
 
6.8%
준 3
 
5.1%
예 3
 
5.1%
Other values (13) 17
28.8%
Decimal Number
ValueCountFrequency (%)
2 8
47.1%
0 3
 
17.6%
5 2
 
11.8%
1 2
 
11.8%
6 1
 
5.9%
4 1
 
5.9%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59
63.4%
Common 34
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 8
13.6%
수 4
 
6.8%
장 4
 
6.8%
정 4
 
6.8%
체 4
 
6.8%
업 4
 
6.8%
록 4
 
6.8%
등 4
 
6.8%
준 3
 
5.1%
예 3
 
5.1%
Other values (13) 17
28.8%
Common
ValueCountFrequency (%)
11
32.4%
2 8
23.5%
. 6
17.6%
0 3
 
8.8%
5 2
 
5.9%
1 2
 
5.9%
6 1
 
2.9%
4 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59
63.4%
ASCII 34
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
32.4%
2 8
23.5%
. 6
17.6%
0 3
 
8.8%
5 2
 
5.9%
1 2
 
5.9%
6 1
 
2.9%
4 1
 
2.9%
Hangul
ValueCountFrequency (%)
공 8
13.6%
수 4
 
6.8%
장 4
 
6.8%
정 4
 
6.8%
체 4
 
6.8%
업 4
 
6.8%
록 4
 
6.8%
등 4
 
6.8%
준 3
 
5.1%
예 3
 
5.1%
Other values (13) 17
28.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size576.0 B
Minimum2024-02-28 00:00:00
Maximum2024-02-28 00:00:00
2024-03-14T20:27:25.892088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:27:26.185357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T20:27:12.644375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:27:12.125422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:27:12.910639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:27:12.396431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:27:26.608122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지식산업센터명칭소재지지번주소소재지도로명주소용도지역건축연면적(제곱미터)입주업체수비고
지식산업센터명칭1.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.000
용도지역1.0001.0001.0001.0000.2160.0000.000
건축연면적(제곱미터)1.0001.0001.0000.2161.0000.7230.533
입주업체수1.0001.0001.0000.0000.7231.0000.000
비고1.0001.0001.0000.0000.5330.0001.000
2024-03-14T20:27:26.887314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축연면적(제곱미터)입주업체수용도지역
건축연면적(제곱미터)1.0000.6910.127
입주업체수0.6911.0000.000
용도지역0.1270.0001.000

Missing values

2024-03-14T20:27:13.238803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:27:13.696212image/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.
2024-03-14T20:27:14.011286image/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

시군명지식산업센터명칭소재지지번주소소재지도로명주소용도지역건축연면적(제곱미터)입주업체수비고데이터기준일
0성남시분당테크노파크경기도 성남시 분당구 야탑동 145경기도 성남시 분당구 판교로 697근린상업193217138공장등록업체수2024-02-28
1성남시남서울첨단경기도 성남시 분당구 백현동 404-1경기도 성남시 분당구 대왕판교로 395번길8자연녹지104961공장등록업체수2024-02-28
2성남시반도아이비밸리경기도 성남시 수정구 고등동 603경기도 성남시 수정구 청계산로 686근린상업4154413공장등록업체수2024-02-28
3성남시현대지식산업센터경기도 성남시 수정구 고등동 572경기도 성남시 수정구 고등로 3준주거지역4991513공장등록업체수2024-02-28
4성남시LH기업성장센터경기도 성남시 수정구 시흥동 294-2경기도 성남시 수정구 창업로 54준공업지역53053120<NA>2024-02-28
5성남시경기기업성장센터(GICO)경기도 성남시 수정구 시흥동 293경기도 성남시 수정구 창업로 42준공업지역70598117<NA>2024-02-28
6성남시판교이노베이션랩경기도 성남시 수정구 금토동 411-6경기도 성남시 수정구 금토로80번길 11준주거지역5766822<NA>2024-02-28
7성남시글로벌Biz센터(G5-1)경기도 성남시 수정구 시흥동 293외 8필지판교제2테크노밸리 G5-1복합용지+준주거지역9558848<NA>2024-02-28
8성남시성남글로벌융합센터경기도 성남시 수정구 시흥동 356경기도 성남시 수정구 달래내로 46준공업지역3661712<NA>2024-02-28
9성남시판교IT센터판교제2테크노밸리 E2-1경기도 성남시 수정구 창업로40번길 30준공업지역3835913<NA>2024-02-28
시군명지식산업센터명칭소재지지번주소소재지도로명주소용도지역건축연면적(제곱미터)입주업체수비고데이터기준일
46성남시센트럴 비즈타워경기도 성남시 중원구 상대원동 143-2경기도 성남시 중원구 갈마치로 314일반공업6347197<NA>2024-02-28
47성남시SK V1경기도 성남시 중원구 상대원동 546경기도 성남시 중원구 갈마치로288번길 14일반공업140396217<NA>2024-02-28
48성남시자생메디바이오센터경기도 성남시 중원구 상대원동 567-1경기도 성남시 중원구 사기막골로 18일반공업226764<NA>2024-02-28
49성남시성남 센터엠경기도 성남시 중원구 상대원동 223-27 외 2필지경기도 성남시 중원구 사기막골로62번길 33일반공업70980160<NA>2024-02-28
50성남시센트럴 비즈타워 2차경기도 성남시 중원구 상대원동 145-3경기도 성남시 중원구 사기막골로 99일반공업94465143<NA>2024-02-28
51성남시성우지식산업센터경기도 성남시 중원구 상대원동 510-9경기도 성남시 중원구 갈마치로 176일반공업93112<NA>2024-02-28
52성남시대유지식산업센터경기도 성남시 중원구 상대원동 500-2경기도 성남시 중원구 둔촌대로 509일반공업441680입주자 모집 미공고2024-02-28
53성남시영원패션클러스터경기도 성남시 중원구 상대원동 133-2경기도 성남시 중원구 사기막골로 169일반공업385420입주시기 미확정2024-02-28
54성남시성남 아이파크 디어반경기도 성남시 중원구 상대원동 252-1(복합구역)경기도 성남시 중원구 갈마치로 241준주거지역8348102024. 5. 준공 예정2024-02-28
55성남시센트럴비즈타워3차경기도 성남시 중원구 상대원동 333-5<NA>일반공업6219602025. 12. 준공 예정2024-02-28