Overview

Dataset statistics

Number of variables5
Number of observations311
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.6 KiB
Average record size in memory41.4 B

Variable types

Text3
Numeric1
Categorical1

Dataset

Description군포시 체육시설업 현황에 대한 데이터로 허가변호, 상호명, 소재지주소, 면적, 데이터기준일자 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15016222/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
허가번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:43:23.852905
Analysis finished2023-12-12 12:43:24.458181
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

허가번호
Text

UNIQUE 

Distinct311
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T21:43:24.679878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.9228296
Min length5

Characters and Unicode

Total characters2464
Distinct characters40
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

Unique311 ?
Unique (%)100.0%

Sample

1st row수영장-1
2nd row수영장-3
3rd row수영장-5
4th row수영장-7
5th row수영장-8
ValueCountFrequency (%)
수영장-1 1
 
0.3%
당구장-341 1
 
0.3%
골프연습장-27 1
 
0.3%
골프연습장-25 1
 
0.3%
골프연습장-24 1
 
0.3%
골프연습장-13 1
 
0.3%
골프연습장-11 1
 
0.3%
골프연습장-2 1
 
0.3%
당구장-352 1
 
0.3%
당구장-350 1
 
0.3%
Other values (301) 301
96.8%
2023-12-12T21:43:25.185744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 312
 
12.7%
260
 
10.6%
209
 
8.5%
1 191
 
7.8%
124
 
5.0%
2 97
 
3.9%
3 91
 
3.7%
79
 
3.2%
77
 
3.1%
61
 
2.5%
Other values (30) 963
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1412
57.3%
Decimal Number 740
30.0%
Dash Punctuation 312
 
12.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
260
18.4%
209
14.8%
124
 
8.8%
79
 
5.6%
77
 
5.5%
61
 
4.3%
61
 
4.3%
61
 
4.3%
58
 
4.1%
58
 
4.1%
Other values (19) 364
25.8%
Decimal Number
ValueCountFrequency (%)
1 191
25.8%
2 97
13.1%
3 91
12.3%
0 59
 
8.0%
7 57
 
7.7%
9 56
 
7.6%
5 53
 
7.2%
4 51
 
6.9%
8 48
 
6.5%
6 37
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1412
57.3%
Common 1052
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
260
18.4%
209
14.8%
124
 
8.8%
79
 
5.6%
77
 
5.5%
61
 
4.3%
61
 
4.3%
61
 
4.3%
58
 
4.1%
58
 
4.1%
Other values (19) 364
25.8%
Common
ValueCountFrequency (%)
- 312
29.7%
1 191
18.2%
2 97
 
9.2%
3 91
 
8.7%
0 59
 
5.6%
7 57
 
5.4%
9 56
 
5.3%
5 53
 
5.0%
4 51
 
4.8%
8 48
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1412
57.3%
ASCII 1052
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 312
29.7%
1 191
18.2%
2 97
 
9.2%
3 91
 
8.7%
0 59
 
5.6%
7 57
 
5.4%
9 56
 
5.3%
5 53
 
5.0%
4 51
 
4.8%
8 48
 
4.6%
Hangul
ValueCountFrequency (%)
260
18.4%
209
14.8%
124
 
8.8%
79
 
5.6%
77
 
5.5%
61
 
4.3%
61
 
4.3%
61
 
4.3%
58
 
4.1%
58
 
4.1%
Other values (19) 364
25.8%
Distinct304
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T21:43:25.519948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length8.3440514
Min length3

Characters and Unicode

Total characters2595
Distinct characters333
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

Unique297 ?
Unique (%)95.5%

Sample

1st row한숲스포츠 스포츠센터
2nd row스포츠그린힐 수영장
3rd row군포시노동종합복지관
4th row㈜코리아비젼스윔
5th rowSWIM21 어린이수영장
ValueCountFrequency (%)
태권도장 19
 
3.8%
용인대 10
 
2.0%
경희대 8
 
1.6%
골프 7
 
1.4%
휘트니스 7
 
1.4%
당구장 7
 
1.4%
골프존파크 5
 
1.0%
산본점 5
 
1.0%
국가대표 4
 
0.8%
석사 4
 
0.8%
Other values (367) 423
84.8%
2023-12-12T21:43:26.017095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
 
7.3%
124
 
4.8%
87
 
3.4%
72
 
2.8%
69
 
2.7%
63
 
2.4%
60
 
2.3%
57
 
2.2%
49
 
1.9%
49
 
1.9%
Other values (323) 1776
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2226
85.8%
Space Separator 189
 
7.3%
Uppercase Letter 120
 
4.6%
Lowercase Letter 16
 
0.6%
Close Punctuation 11
 
0.4%
Open Punctuation 10
 
0.4%
Decimal Number 9
 
0.3%
Other Symbol 6
 
0.2%
Other Punctuation 6
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
124
 
5.6%
87
 
3.9%
72
 
3.2%
69
 
3.1%
63
 
2.8%
60
 
2.7%
57
 
2.6%
49
 
2.2%
49
 
2.2%
46
 
2.1%
Other values (276) 1550
69.6%
Uppercase Letter
ValueCountFrequency (%)
G 16
13.3%
S 15
12.5%
T 12
 
10.0%
P 9
 
7.5%
M 8
 
6.7%
I 5
 
4.2%
E 5
 
4.2%
N 5
 
4.2%
A 5
 
4.2%
D 5
 
4.2%
Other values (15) 35
29.2%
Lowercase Letter
ValueCountFrequency (%)
m 3
18.8%
y 3
18.8%
k 2
12.5%
p 2
12.5%
o 2
12.5%
l 1
 
6.2%
g 1
 
6.2%
a 1
 
6.2%
e 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
2 2
 
22.2%
5 1
 
11.1%
6 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
, 2
33.3%
& 1
 
16.7%
Space Separator
ValueCountFrequency (%)
189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2232
86.0%
Common 227
 
8.7%
Latin 136
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
124
 
5.6%
87
 
3.9%
72
 
3.2%
69
 
3.1%
63
 
2.8%
60
 
2.7%
57
 
2.6%
49
 
2.2%
49
 
2.2%
46
 
2.1%
Other values (277) 1556
69.7%
Latin
ValueCountFrequency (%)
G 16
 
11.8%
S 15
 
11.0%
T 12
 
8.8%
P 9
 
6.6%
M 8
 
5.9%
I 5
 
3.7%
E 5
 
3.7%
N 5
 
3.7%
A 5
 
3.7%
D 5
 
3.7%
Other values (24) 51
37.5%
Common
ValueCountFrequency (%)
189
83.3%
) 11
 
4.8%
( 10
 
4.4%
1 5
 
2.2%
. 3
 
1.3%
2 2
 
0.9%
, 2
 
0.9%
5 1
 
0.4%
6 1
 
0.4%
& 1
 
0.4%
Other values (2) 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2226
85.8%
ASCII 363
 
14.0%
None 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
52.1%
G 16
 
4.4%
S 15
 
4.1%
T 12
 
3.3%
) 11
 
3.0%
( 10
 
2.8%
P 9
 
2.5%
M 8
 
2.2%
I 5
 
1.4%
E 5
 
1.4%
Other values (36) 83
22.9%
Hangul
ValueCountFrequency (%)
124
 
5.6%
87
 
3.9%
72
 
3.2%
69
 
3.1%
63
 
2.8%
60
 
2.7%
57
 
2.6%
49
 
2.2%
49
 
2.2%
46
 
2.1%
Other values (276) 1550
69.6%
None
ValueCountFrequency (%)
6
100.0%
Distinct310
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T21:43:26.511987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length42
Mean length30.041801
Min length15

Characters and Unicode

Total characters9343
Distinct characters190
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

Unique309 ?
Unique (%)99.4%

Sample

1st row경기도 군포시 산본천로 43-6, 지층(산본동)
2nd row경기도 군포시 산본로 276, 지층(금정동)
3rd row경기도 군포시 용호1로 21번길 14, 지하3층(당동)
4th row경기도 군포시 번영로 515, 지하1층 (산본동, 유화프라자)
5th row경기도 군포시 광정로58, 지하1층 2호 일부(산본동, 신산본빌딩 지하1층)
ValueCountFrequency (%)
경기도 316
 
17.3%
군포시 312
 
17.1%
산본동 41
 
2.2%
고산로 35
 
1.9%
번영로 26
 
1.4%
산본로 25
 
1.4%
3층 24
 
1.3%
당동 20
 
1.1%
군포로 20
 
1.1%
2층 18
 
1.0%
Other values (562) 987
54.1%
2023-12-12T21:43:27.204946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1519
 
16.3%
, 385
 
4.1%
1 375
 
4.0%
349
 
3.7%
347
 
3.7%
328
 
3.5%
320
 
3.4%
2 320
 
3.4%
317
 
3.4%
316
 
3.4%
Other values (180) 4767
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4862
52.0%
Decimal Number 1983
21.2%
Space Separator 1519
 
16.3%
Other Punctuation 391
 
4.2%
Open Punctuation 236
 
2.5%
Close Punctuation 236
 
2.5%
Dash Punctuation 67
 
0.7%
Uppercase Letter 34
 
0.4%
Math Symbol 12
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
349
 
7.2%
347
 
7.1%
328
 
6.7%
320
 
6.6%
317
 
6.5%
316
 
6.5%
310
 
6.4%
255
 
5.2%
251
 
5.2%
187
 
3.8%
Other values (151) 1882
38.7%
Decimal Number
ValueCountFrequency (%)
1 375
18.9%
2 320
16.1%
3 277
14.0%
0 271
13.7%
4 192
9.7%
5 175
8.8%
6 154
7.8%
7 91
 
4.6%
8 72
 
3.6%
9 56
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
B 11
32.4%
S 5
14.7%
G 4
 
11.8%
A 3
 
8.8%
K 3
 
8.8%
C 3
 
8.8%
L 2
 
5.9%
D 2
 
5.9%
E 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 385
98.5%
. 5
 
1.3%
& 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1519
100.0%
Open Punctuation
ValueCountFrequency (%)
( 236
100.0%
Close Punctuation
ValueCountFrequency (%)
) 236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4862
52.0%
Common 4444
47.6%
Latin 37
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
349
 
7.2%
347
 
7.1%
328
 
6.7%
320
 
6.6%
317
 
6.5%
316
 
6.5%
310
 
6.4%
255
 
5.2%
251
 
5.2%
187
 
3.8%
Other values (151) 1882
38.7%
Common
ValueCountFrequency (%)
1519
34.2%
, 385
 
8.7%
1 375
 
8.4%
2 320
 
7.2%
3 277
 
6.2%
0 271
 
6.1%
( 236
 
5.3%
) 236
 
5.3%
4 192
 
4.3%
5 175
 
3.9%
Other values (8) 458
 
10.3%
Latin
ValueCountFrequency (%)
B 11
29.7%
S 5
13.5%
G 4
 
10.8%
A 3
 
8.1%
K 3
 
8.1%
C 3
 
8.1%
b 2
 
5.4%
L 2
 
5.4%
D 2
 
5.4%
E 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4862
52.0%
ASCII 4480
48.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1519
33.9%
, 385
 
8.6%
1 375
 
8.4%
2 320
 
7.1%
3 277
 
6.2%
0 271
 
6.0%
( 236
 
5.3%
) 236
 
5.3%
4 192
 
4.3%
5 175
 
3.9%
Other values (18) 494
 
11.0%
Hangul
ValueCountFrequency (%)
349
 
7.2%
347
 
7.1%
328
 
6.7%
320
 
6.6%
317
 
6.5%
316
 
6.5%
310
 
6.4%
255
 
5.2%
251
 
5.2%
187
 
3.8%
Other values (151) 1882
38.7%
Number Forms
ValueCountFrequency (%)
1
100.0%

면적
Real number (ℝ)

Distinct304
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3234.2011
Minimum41.58
Maximum878287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T21:43:27.399493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41.58
5-th percentile102.27
Q1152.845
median234.81
Q3381.255
95-th percentile842.72
Maximum878287
Range878245.42
Interquartile range (IQR)228.41

Descriptive statistics

Standard deviation49799.963
Coefficient of variation (CV)15.397918
Kurtosis310.49071
Mean3234.2011
Median Absolute Deviation (MAD)89.83
Skewness17.613943
Sum1005836.6
Variance2.4800363 × 109
MonotonicityNot monotonic
2023-12-12T21:43:27.566677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
175.82 2
 
0.6%
286.95 2
 
0.6%
99.0 2
 
0.6%
162.0 2
 
0.6%
165.0 2
 
0.6%
108.0 2
 
0.6%
175.0 2
 
0.6%
1383.39 1
 
0.3%
768.2 1
 
0.3%
409.863 1
 
0.3%
Other values (294) 294
94.5%
ValueCountFrequency (%)
41.58 1
0.3%
55.28 1
0.3%
55.582 1
0.3%
60.04 1
0.3%
71.76 1
0.3%
75.98 1
0.3%
80.64 1
0.3%
87.01 1
0.3%
91.0 1
0.3%
91.26 1
0.3%
ValueCountFrequency (%)
878287.0 1
0.3%
23900.0 1
0.3%
7081.96 1
0.3%
2357.6 1
0.3%
1642.0 1
0.3%
1610.0 1
0.3%
1570.27 1
0.3%
1542.2 1
0.3%
1420.7 1
0.3%
1383.39 1
0.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-05-31
311 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-31
2nd row2023-05-31
3rd row2023-05-31
4th row2023-05-31
5th row2023-05-31

Common Values

ValueCountFrequency (%)
2023-05-31 311
100.0%

Length

2023-12-12T21:43:27.727236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:43:27.839585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-31 311
100.0%

Interactions

2023-12-12T21:43:24.193067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T21:43:24.315996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:43:24.418904image/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

허가번호상호명소재지주소면적데이터기준일자
0수영장-1한숲스포츠 스포츠센터경기도 군포시 산본천로 43-6, 지층(산본동)1383.392023-05-31
1수영장-3스포츠그린힐 수영장경기도 군포시 산본로 276, 지층(금정동)2357.62023-05-31
2수영장-5군포시노동종합복지관경기도 군포시 용호1로 21번길 14, 지하3층(당동)1570.272023-05-31
3수영장-7㈜코리아비젼스윔경기도 군포시 번영로 515, 지하1층 (산본동, 유화프라자)786.852023-05-31
4수영장-8SWIM21 어린이수영장경기도 군포시 광정로58, 지하1층 2호 일부(산본동, 신산본빌딩 지하1층)495.432023-05-31
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6수영장-10군포시청소년수련관경기도 군포시 산본로 322(금정동)1610.02023-05-31
7수영장-11군포국민체육센터 수영장경기도 군포시 군포로 339, 지하1층(부곡동)1642.02023-05-31
8수영장-12부곡체육시설 수영장경기도 군포시 군포첨단산업2로22번길 5, 지층(부곡동)1262.02023-05-31
9무도학원-1두리댄스스포츠경기도 군포시 산본로323번길13, 806호(산본동)95.342023-05-31
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301체육교습업-19한국파워점핑줄넘기경기도 군포시 광정로 59, 404호123.482023-05-31
302체육교습업-20패스체대입시 산본안양센터경기도 군포시 광정로 70, 지하2층127.582023-05-31
303체육교습업-21군포시리틀야구단경기도 군포시 군포로 464번길19 두산(아)상가 지하1층 (당동)357.162023-05-31
304체육교습업-22워너비베이스볼경기도 군포시 엘에스로182번길26, 2층(산본동)495.082023-05-31
305체육교습업-23킹콩점핑줄넘기경기도 군포시 금산로 74, 2층(산본동)114.482023-05-31
306체육교습업-24빌드업 풋볼 클럽경기도 군포시 군포첨단산업2로 7번길 8, B동 201호155.72023-05-31
307체육교습업-25바스농구클럽경기도 군포시 고산로 126번길 18, 2층457.982023-05-31
308체육교습업-26아이스포렉스경기도 군포시 용호1로16번길 26, 지하1층 (당동, 럭키유치원)278.462023-05-31
309인공암벽장업-1볼더팝경기도 군포시 공단로104번길 11, 1층436.932023-05-31
310인공암벽장업-3산본클라이밍센터경기도 군포시 고산로 695, 604호(산본동)152.792023-05-31