Overview

Dataset statistics

Number of variables6
Number of observations801
Missing cells407
Missing cells (%)8.5%
Duplicate rows2
Duplicate rows (%)0.2%
Total size in memory37.7 KiB
Average record size in memory48.2 B

Variable types

Categorical2
Text4

Dataset

Description인천광역시 서구 체육시설업 현황에 대한 데이터셋입니다. 인천광역시 서구 체육시설업 현황 및 업종, 상호, 시설주소, 전화번호 등에 대한 정보를 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3044203&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 2 (0.2%) duplicate rowsDuplicates
전화번호 has 400 (49.9%) missing valuesMissing

Reproduction

Analysis started2024-04-17 09:06:23.076146
Analysis finished2024-04-17 09:06:23.780194
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct13
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
체육도장업
224 
당구장업
218 
체력단련장업
143 
골프연습장업
89 
가상체험 체육시설업
61 
Other values (8)
66 

Length

Max length10
Median length7
Mean length5.3832709
Min length4

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
체육도장업 224
28.0%
당구장업 218
27.2%
체력단련장업 143
17.9%
골프연습장업 89
 
11.1%
가상체험 체육시설업 61
 
7.6%
체육교습업 42
 
5.2%
수영장업 11
 
1.4%
야구장업 4
 
0.5%
무도학원업 3
 
0.4%
인공암벽장업 3
 
0.4%
Other values (3) 3
 
0.4%

Length

2024-04-17T18:06:23.835476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
체육도장업 224
26.0%
당구장업 218
25.3%
체력단련장업 143
16.6%
골프연습장업 89
 
10.3%
가상체험 61
 
7.1%
체육시설업 61
 
7.1%
체육교습업 42
 
4.9%
수영장업 11
 
1.3%
야구장업 4
 
0.5%
무도학원업 3
 
0.3%
Other values (4) 6
 
0.7%

상호
Text

Distinct767
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-17T18:06:24.047458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length8.0411985
Min length2

Characters and Unicode

Total characters6441
Distinct characters490
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique741 ?
Unique (%)92.5%

Sample

1st row검단복지회관 수영장
2nd row블루라군
3rd row포세이돈 스위밍 아카데미
4th row검단오션차일드
5th row마린어린이수영장
ValueCountFrequency (%)
태권도장 58
 
4.4%
당구클럽 42
 
3.2%
당구장 36
 
2.7%
태권도 24
 
1.8%
용인대 19
 
1.5%
아카데미 17
 
1.3%
경희대 15
 
1.1%
청라 11
 
0.8%
골프 8
 
0.6%
청라점 8
 
0.6%
Other values (879) 1072
81.8%
2024-04-17T18:06:24.378099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
509
 
7.9%
장 260
 
4.0%
구 234
 
3.6%
스 215
 
3.3%
당 210
 
3.3%
도 198
 
3.1%
태 176
 
2.7%
권 163
 
2.5%
프 147
 
2.3%
클 131
 
2.0%
Other values (480) 4198
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5311
82.5%
Space Separator 509
 
7.9%
Uppercase Letter 360
 
5.6%
Lowercase Letter 84
 
1.3%
Decimal Number 51
 
0.8%
Open Punctuation 44
 
0.7%
Close Punctuation 44
 
0.7%
Other Punctuation 34
 
0.5%
Dash Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 260
 
4.9%
구 234
 
4.4%
스 215
 
4.0%
당 210
 
4.0%
도 198
 
3.7%
태 176
 
3.3%
권 163
 
3.1%
프 147
 
2.8%
클 131
 
2.5%
럽 128
 
2.4%
Other values (412) 3449
64.9%
Uppercase Letter
ValueCountFrequency (%)
S 49
13.6%
G 32
 
8.9%
B 30
 
8.3%
T 27
 
7.5%
M 21
 
5.8%
I 19
 
5.3%
K 19
 
5.3%
C 18
 
5.0%
A 17
 
4.7%
P 17
 
4.7%
Other values (16) 111
30.8%
Lowercase Letter
ValueCountFrequency (%)
o 12
14.3%
e 8
 
9.5%
s 7
 
8.3%
a 5
 
6.0%
r 5
 
6.0%
y 5
 
6.0%
n 4
 
4.8%
m 4
 
4.8%
i 4
 
4.8%
l 4
 
4.8%
Other values (10) 26
31.0%
Decimal Number
ValueCountFrequency (%)
2 13
25.5%
1 11
21.6%
0 7
13.7%
4 4
 
7.8%
5 4
 
7.8%
6 3
 
5.9%
8 3
 
5.9%
9 2
 
3.9%
7 2
 
3.9%
3 2
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 11
32.4%
& 10
29.4%
, 4
 
11.8%
' 4
 
11.8%
· 3
 
8.8%
/ 1
 
2.9%
: 1
 
2.9%
Space Separator
ValueCountFrequency (%)
509
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
＋ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5309
82.4%
Common 686
 
10.7%
Latin 444
 
6.9%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 260
 
4.9%
구 234
 
4.4%
스 215
 
4.0%
당 210
 
4.0%
도 198
 
3.7%
태 176
 
3.3%
권 163
 
3.1%
프 147
 
2.8%
클 131
 
2.5%
럽 128
 
2.4%
Other values (411) 3447
64.9%
Latin
ValueCountFrequency (%)
S 49
 
11.0%
G 32
 
7.2%
B 30
 
6.8%
T 27
 
6.1%
M 21
 
4.7%
I 19
 
4.3%
K 19
 
4.3%
C 18
 
4.1%
A 17
 
3.8%
P 17
 
3.8%
Other values (36) 195
43.9%
Common
ValueCountFrequency (%)
509
74.2%
( 44
 
6.4%
) 44
 
6.4%
2 13
 
1.9%
1 11
 
1.6%
. 11
 
1.6%
& 10
 
1.5%
0 7
 
1.0%
4 4
 
0.6%
, 4
 
0.6%
Other values (12) 29
 
4.2%
Han
ValueCountFrequency (%)
秀 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5309
82.4%
ASCII 1126
 
17.5%
None 4
 
0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
509
45.2%
S 49
 
4.4%
( 44
 
3.9%
) 44
 
3.9%
G 32
 
2.8%
B 30
 
2.7%
T 27
 
2.4%
M 21
 
1.9%
I 19
 
1.7%
K 19
 
1.7%
Other values (56) 332
29.5%
Hangul
ValueCountFrequency (%)
장 260
 
4.9%
구 234
 
4.4%
스 215
 
4.0%
당 210
 
4.0%
도 198
 
3.7%
태 176
 
3.3%
권 163
 
3.1%
프 147
 
2.8%
클 131
 
2.5%
럽 128
 
2.4%
Other values (411) 3447
64.9%
None
ValueCountFrequency (%)
· 3
75.0%
＋ 1
 
25.0%
CJK
ValueCountFrequency (%)
秀 2
100.0%

시설주소(지번)
Text

Distinct718
Distinct (%)89.8%
Missing1
Missing (%)0.1%
Memory size6.4 KiB
2024-04-17T18:06:24.632764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length24.815
Min length16

Characters and Unicode

Total characters19852
Distinct characters298
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique658 ?
Unique (%)82.2%

Sample

1st row인천광역시 서구 마전동 산 147
2nd row인천광역시 서구 청라동 130-4
3rd row인천광역시 서구 청라동 163-3 홍익파크 802호
4th row인천광역시 서구 당하동 895-1 상가동 지101호
5th row인천광역시 서구 경서동 726-1
ValueCountFrequency (%)
인천광역시 800
19.6%
서구 800
19.6%
청라동 163
 
4.0%
가좌동 95
 
2.3%
석남동 83
 
2.0%
마전동 69
 
1.7%
당하동 61
 
1.5%
심곡동 51
 
1.3%
가정동 51
 
1.3%
2층 47
 
1.2%
Other values (1030) 1857
45.5%
2024-04-17T18:06:24.988494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3973
20.0%
1 877
 
4.4%
구 837
 
4.2%
동 826
 
4.2%
서 822
 
4.1%
시 813
 
4.1%
인 811
 
4.1%
천 805
 
4.1%
광 801
 
4.0%
역 800
 
4.0%
Other values (288) 8487
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10583
53.3%
Decimal Number 4351
21.9%
Space Separator 3973
 
20.0%
Dash Punctuation 692
 
3.5%
Other Punctuation 74
 
0.4%
Uppercase Letter 73
 
0.4%
Open Punctuation 34
 
0.2%
Close Punctuation 34
 
0.2%
Lowercase Letter 28
 
0.1%
Math Symbol 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 837
 
7.9%
동 826
 
7.8%
서 822
 
7.8%
시 813
 
7.7%
인 811
 
7.7%
천 805
 
7.6%
광 801
 
7.6%
역 800
 
7.6%
라 353
 
3.3%
청 199
 
1.9%
Other values (243) 3516
33.2%
Uppercase Letter
ValueCountFrequency (%)
L 11
15.1%
K 10
13.7%
B 8
11.0%
E 5
 
6.8%
M 5
 
6.8%
S 5
 
6.8%
W 4
 
5.5%
A 4
 
5.5%
I 4
 
5.5%
V 4
 
5.5%
Other values (8) 13
17.8%
Decimal Number
ValueCountFrequency (%)
1 877
20.2%
2 606
13.9%
0 544
12.5%
3 440
10.1%
5 402
9.2%
6 343
 
7.9%
4 340
 
7.8%
7 290
 
6.7%
8 255
 
5.9%
9 254
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
e 8
28.6%
a 5
17.9%
r 5
17.9%
d 4
14.3%
s 4
14.3%
k 1
 
3.6%
b 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 66
89.2%
' 4
 
5.4%
@ 2
 
2.7%
. 1
 
1.4%
& 1
 
1.4%
Space Separator
ValueCountFrequency (%)
3973
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 692
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10583
53.3%
Common 9168
46.2%
Latin 101
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 837
 
7.9%
동 826
 
7.8%
서 822
 
7.8%
시 813
 
7.7%
인 811
 
7.7%
천 805
 
7.6%
광 801
 
7.6%
역 800
 
7.6%
라 353
 
3.3%
청 199
 
1.9%
Other values (243) 3516
33.2%
Latin
ValueCountFrequency (%)
L 11
 
10.9%
K 10
 
9.9%
e 8
 
7.9%
B 8
 
7.9%
a 5
 
5.0%
E 5
 
5.0%
M 5
 
5.0%
r 5
 
5.0%
S 5
 
5.0%
W 4
 
4.0%
Other values (15) 35
34.7%
Common
ValueCountFrequency (%)
3973
43.3%
1 877
 
9.6%
- 692
 
7.5%
2 606
 
6.6%
0 544
 
5.9%
3 440
 
4.8%
5 402
 
4.4%
6 343
 
3.7%
4 340
 
3.7%
7 290
 
3.2%
Other values (10) 661
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10583
53.3%
ASCII 9269
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3973
42.9%
1 877
 
9.5%
- 692
 
7.5%
2 606
 
6.5%
0 544
 
5.9%
3 440
 
4.7%
5 402
 
4.3%
6 343
 
3.7%
4 340
 
3.7%
7 290
 
3.1%
Other values (35) 762
 
8.2%
Hangul
ValueCountFrequency (%)
구 837
 
7.9%
동 826
 
7.8%
서 822
 
7.8%
시 813
 
7.7%
인 811
 
7.7%
천 805
 
7.6%
광 801
 
7.6%
역 800
 
7.6%
라 353
 
3.3%
청 199
 
1.9%
Other values (243) 3516
33.2%

시설주소(도로명)
Text

Distinct778
Distinct (%)97.9%
Missing6
Missing (%)0.7%
Memory size6.4 KiB
2024-04-17T18:06:25.232814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length52
Mean length33.993711
Min length21

Characters and Unicode

Total characters27025
Distinct characters341
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique762 ?
Unique (%)95.8%

Sample

1st row인천광역시 서구 완정로92번길 18 (마전동)
2nd row인천광역시 서구 청라에메랄드로 134, 상가동 지하1층 101호 (연희동, 호반베르디움앤영무예다움 )
3rd row인천광역시 서구 중봉대로586번길 19, 8층 802호 (연희동, 홍익파크)
4th row인천광역시 서구 서곶로 818, 상가동 지하1층 지하101호 (당하동, 영남탑스빌아파트)
5th row인천광역시 서구 경서로 80, 지하1층층 (경서동)
ValueCountFrequency (%)
인천광역시 795
 
15.4%
서구 795
 
15.4%
청라동 90
 
1.7%
2층 83
 
1.6%
3층 78
 
1.5%
가좌동 71
 
1.4%
마전동 66
 
1.3%
석남동 64
 
1.2%
연희동 63
 
1.2%
당하동 58
 
1.1%
Other values (1158) 2988
58.0%
2024-04-17T18:06:25.600795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4437
 
16.4%
, 1029
 
3.8%
서 896
 
3.3%
동 852
 
3.2%
1 845
 
3.1%
로 827
 
3.1%
( 814
 
3.0%
) 814
 
3.0%
인 813
 
3.0%
시 809
 
3.0%
Other values (331) 14889
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14715
54.4%
Decimal Number 4961
 
18.4%
Space Separator 4437
 
16.4%
Other Punctuation 1037
 
3.8%
Open Punctuation 814
 
3.0%
Close Punctuation 814
 
3.0%
Dash Punctuation 112
 
0.4%
Uppercase Letter 69
 
0.3%
Math Symbol 36
 
0.1%
Lowercase Letter 30
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 896
 
6.1%
동 852
 
5.8%
로 827
 
5.6%
인 813
 
5.5%
시 809
 
5.5%
천 804
 
5.5%
구 800
 
5.4%
광 797
 
5.4%
역 795
 
5.4%
라 451
 
3.1%
Other values (288) 6871
46.7%
Uppercase Letter
ValueCountFrequency (%)
K 12
17.4%
B 10
14.5%
M 8
11.6%
E 5
7.2%
L 5
7.2%
S 5
7.2%
W 4
 
5.8%
I 4
 
5.8%
V 4
 
5.8%
A 3
 
4.3%
Other values (6) 9
13.0%
Decimal Number
ValueCountFrequency (%)
1 845
17.0%
0 739
14.9%
2 732
14.8%
3 581
11.7%
4 462
9.3%
5 359
7.2%
7 348
7.0%
6 340
6.9%
8 310
 
6.2%
9 245
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 9
30.0%
r 5
16.7%
a 5
16.7%
d 4
13.3%
s 4
13.3%
k 2
 
6.7%
b 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 1029
99.2%
' 4
 
0.4%
@ 2
 
0.2%
. 1
 
0.1%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4437
100.0%
Open Punctuation
ValueCountFrequency (%)
( 814
100.0%
Close Punctuation
ValueCountFrequency (%)
) 814
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Math Symbol
ValueCountFrequency (%)
~ 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14715
54.4%
Common 12211
45.2%
Latin 99
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 896
 
6.1%
동 852
 
5.8%
로 827
 
5.6%
인 813
 
5.5%
시 809
 
5.5%
천 804
 
5.5%
구 800
 
5.4%
광 797
 
5.4%
역 795
 
5.4%
라 451
 
3.1%
Other values (288) 6871
46.7%
Latin
ValueCountFrequency (%)
K 12
 
12.1%
B 10
 
10.1%
e 9
 
9.1%
M 8
 
8.1%
r 5
 
5.1%
a 5
 
5.1%
E 5
 
5.1%
L 5
 
5.1%
S 5
 
5.1%
d 4
 
4.0%
Other values (13) 31
31.3%
Common
ValueCountFrequency (%)
4437
36.3%
, 1029
 
8.4%
1 845
 
6.9%
( 814
 
6.7%
) 814
 
6.7%
0 739
 
6.1%
2 732
 
6.0%
3 581
 
4.8%
4 462
 
3.8%
5 359
 
2.9%
Other values (10) 1399
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14715
54.4%
ASCII 12310
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4437
36.0%
, 1029
 
8.4%
1 845
 
6.9%
( 814
 
6.6%
) 814
 
6.6%
0 739
 
6.0%
2 732
 
5.9%
3 581
 
4.7%
4 462
 
3.8%
5 359
 
2.9%
Other values (33) 1498
 
12.2%
Hangul
ValueCountFrequency (%)
서 896
 
6.1%
동 852
 
5.8%
로 827
 
5.6%
인 813
 
5.5%
시 809
 
5.5%
천 804
 
5.5%
구 800
 
5.4%
광 797
 
5.4%
역 795
 
5.4%
라 451
 
3.1%
Other values (288) 6871
46.7%

전화번호
Text

MISSING 

Distinct389
Distinct (%)97.0%
Missing400
Missing (%)49.9%
Memory size6.4 KiB
2024-04-17T18:06:25.787952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.032419
Min length12

Characters and Unicode

Total characters4825
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

Unique381 ?
Unique (%)95.0%

Sample

1st row032-561-4115
2nd row032-715-6688
3rd row032-569-4320
4th row032-566-9985
5th row032-721-7676
ValueCountFrequency (%)
070-8640-6335 5
 
1.2%
032-560-9971 3
 
0.7%
032-576-6611 2
 
0.5%
032-568-9345 2
 
0.5%
032-577-8630 2
 
0.5%
032-564-2920 2
 
0.5%
032-562-1819 2
 
0.5%
032-569-2279 2
 
0.5%
032-581-1399 1
 
0.2%
032-575-2322 1
 
0.2%
Other values (379) 379
94.5%
2024-04-17T18:06:26.074675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 802
16.6%
0 670
13.9%
2 588
12.2%
3 578
12.0%
5 575
11.9%
6 426
8.8%
7 368
7.6%
8 231
 
4.8%
1 226
 
4.7%
9 214
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4023
83.4%
Dash Punctuation 802
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 670
16.7%
2 588
14.6%
3 578
14.4%
5 575
14.3%
6 426
10.6%
7 368
9.1%
8 231
 
5.7%
1 226
 
5.6%
9 214
 
5.3%
4 147
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 802
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4825
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 802
16.6%
0 670
13.9%
2 588
12.2%
3 578
12.0%
5 575
11.9%
6 426
8.8%
7 368
7.6%
8 231
 
4.8%
1 226
 
4.7%
9 214
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 802
16.6%
0 670
13.9%
2 588
12.2%
3 578
12.0%
5 575
11.9%
6 426
8.8%
7 368
7.6%
8 231
 
4.8%
1 226
 
4.7%
9 214
 
4.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2022-09-02
801 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-02
2nd row2022-09-02
3rd row2022-09-02
4th row2022-09-02
5th row2022-09-02

Common Values

ValueCountFrequency (%)
2022-09-02 801
100.0%

Length

2024-04-17T18:06:26.182493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:06:26.255432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-02 801
100.0%

Missing values

2024-04-17T18:06:23.580890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T18:06:23.661334image/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.
2024-04-17T18:06:23.736025image/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

업종상호시설주소(지번)시설주소(도로명)전화번호데이터기준일자
0수영장업검단복지회관 수영장인천광역시 서구 마전동 산 147인천광역시 서구 완정로92번길 18 (마전동)032-561-41152022-09-02
1수영장업블루라군인천광역시 서구 청라동 130-4인천광역시 서구 청라에메랄드로 134, 상가동 지하1층 101호 (연희동, 호반베르디움앤영무예다움 )032-715-66882022-09-02
2수영장업포세이돈 스위밍 아카데미인천광역시 서구 청라동 163-3 홍익파크 802호인천광역시 서구 중봉대로586번길 19, 8층 802호 (연희동, 홍익파크)032-569-43202022-09-02
3수영장업검단오션차일드인천광역시 서구 당하동 895-1 상가동 지101호인천광역시 서구 서곶로 818, 상가동 지하1층 지하101호 (당하동, 영남탑스빌아파트)032-566-99852022-09-02
4수영장업마린어린이수영장인천광역시 서구 경서동 726-1인천광역시 서구 경서로 80, 지하1층층 (경서동)<NA>2022-09-02
5수영장업그로윈 스윔 아카데미인천광역시 서구 청라동 157-18 반안프라자 3차인천광역시 서구 청라커낼로260번길 7-15, 반안프라자 3차 7층 (청라동)<NA>2022-09-02
6수영장업(주)슈퍼스타스위밍아카데미인천광역시 서구 가정동 618-5 MK타워인천광역시 서구 봉오재3로94번길 11, MK타워 602,607호 (가정동)032-721-76762022-09-02
7수영장업국제키즈스포츠스쿨인천광역시 서구 청라동 173-1 청라29블럭호반베르디움인천광역시 서구 청라커낼로 163, 301동 지하1층 9~10호 (청라동, 청라29블럭호반베르디움)<NA>2022-09-02
8수영장업ATS스포츠센터-판다수영아카데미 검단점인천광역시 서구 마전동 1005-6 올댓스윔인천광역시 서구 완정로34번길 57-21, 올댓스윔 1층 (마전동)032-563-11052022-09-02
9수영장업SKYSWIMMING & KIZ인천광역시 서구 청라동 96-2인천광역시 서구 청라한내로 90, Mk뷰 8층 (청라동)<NA>2022-09-02
업종상호시설주소(지번)시설주소(도로명)전화번호데이터기준일자
791체육교습업인천서구리틀인천광역시 서구 백석동 58인천광역시 서구 자원순환로 170 (백석동)<NA>2022-09-02
792체육교습업꿀민턴 스포츠센터인천광역시 서구 오류동 1726-9인천광역시 서구 봉화로 33, 2층 (오류동)<NA>2022-09-02
793체육교습업점프업 줄넘기 전문학원인천광역시 서구 원당동 0 ABM타워인천광역시 서구 이음대로 388, ABM타워 717, 718호 (원당동)<NA>2022-09-02
794체육교습업인천서구 청라리틀야구단인천광역시 서구 백석동 58 수도권매립지공사인천광역시 서구 자원순환로 170, 수도권매립지공사 (백석동)<NA>2022-09-02
795체육교습업케이티와이 농구클럽인천광역시 서구 경서동 350-53인천광역시 서구 중봉대로771번길 12 (경서동)<NA>2022-09-02
796체육교습업아라줄넘기·해동검도·검무예인천광역시 서구 원당동 0 정인프라자인천광역시 서구 이음5로 62, 정인프라자 801호 (원당동)032-555-55592022-09-02
797체육교습업더 퍼스트 스포츠 에듀케이션인천광역시 서구 청라동 105-57인천광역시 서구 푸른로7번길 9, 2층 (청라동)<NA>2022-09-02
798인공암벽장업서인천 클라이밍 센터인천광역시 서구 가정동 505-24인천광역시 서구 가정로 374, 4층 (가정동)032-572-88472022-09-02
799인공암벽장업디스커버리씨에스(주) 청라지점인천광역시 서구 청라동 162-10 진영메디피아인천광역시 서구 청라라임로 71, 진영메디피아 1002,1003호 (청라동)032-721-50142022-09-02
800인공암벽장업디스커버리씨에스(주)지점인천광역시 서구 마전동 999-4인천광역시 서구 완정로 70, 5층 (마전동)032-715-50142022-09-02

Duplicate rows

Most frequently occurring

업종상호시설주소(지번)시설주소(도로명)전화번호데이터기준일자# duplicates
1체육교습업코리아 농구교실인천광역시 서구 백석동 212-221인천광역시 서구 한서로 22, 1동 (백석동)<NA>2022-09-023
0가상체험 체육시설업골프존파크스크린연습장인천광역시 서구 원창동 381-76 북항프라자인천광역시 서구 북항로32번안길 8, 북항프라자 708-2,709,710,711-1호 (원창동)<NA>2022-09-022