Overview

Dataset statistics

Number of variables5
Number of observations454
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.3 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Text3
DateTime1

Dataset

Description경상북도 구미시 관내 등록된 인터넷 컴퓨터 시설 제공업 현황에 대한 데이터로 상호명, 소재지 주소 등을 제공하고 있습니다.
URLhttps://www.data.go.kr/data/3071478/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:58:58.113942
Analysis finished2023-12-12 19:58:58.927366
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct454
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.5
Minimum1
Maximum454
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-13T04:58:59.038573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23.65
Q1114.25
median227.5
Q3340.75
95-th percentile431.35
Maximum454
Range453
Interquartile range (IQR)226.5

Descriptive statistics

Standard deviation131.20277
Coefficient of variation (CV)0.57671547
Kurtosis-1.2
Mean227.5
Median Absolute Deviation (MAD)113.5
Skewness0
Sum103285
Variance17214.167
MonotonicityStrictly increasing
2023-12-13T04:58:59.225793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
286 1
 
0.2%
312 1
 
0.2%
311 1
 
0.2%
310 1
 
0.2%
309 1
 
0.2%
308 1
 
0.2%
307 1
 
0.2%
306 1
 
0.2%
305 1
 
0.2%
Other values (444) 444
97.8%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
454 1
0.2%
453 1
0.2%
452 1
0.2%
451 1
0.2%
450 1
0.2%
449 1
0.2%
448 1
0.2%
447 1
0.2%
446 1
0.2%
445 1
0.2%

상호
Text

Distinct388
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-13T04:58:59.589787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5.7180617
Min length2

Characters and Unicode

Total characters2596
Distinct characters364
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

Unique341 ?
Unique (%)75.1%

Sample

1st rowPC BOX
2nd row이게PC방이다 사곡점
3rd rowEX PC
4th row이게PC방이다 임은점
5th row이게PC방이다 본점
ValueCountFrequency (%)
pc 29
 
5.4%
pc방 16
 
3.0%
이게pc방이다 14
 
2.6%
ex 8
 
1.5%
올벤pc방 6
 
1.1%
대박pc 5
 
0.9%
명품pc 4
 
0.7%
도그pc 4
 
0.7%
잘란pc방 3
 
0.6%
쨈나pc방 3
 
0.6%
Other values (391) 447
82.9%
2023-12-13T04:59:00.104735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 429
 
16.5%
C 427
 
16.4%
방 125
 
4.8%
85
 
3.3%
이 55
 
2.1%
드 39
 
1.5%
스 38
 
1.5%
점 37
 
1.4%
게 30
 
1.2%
다 27
 
1.0%
Other values (354) 1304
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1436
55.3%
Uppercase Letter 981
37.8%
Space Separator 85
 
3.3%
Lowercase Letter 60
 
2.3%
Decimal Number 26
 
1.0%
Other Punctuation 4
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 125
 
8.7%
이 55
 
3.8%
드 39
 
2.7%
스 38
 
2.6%
점 37
 
2.6%
게 30
 
2.1%
다 27
 
1.9%
롯 21
 
1.5%
랜 21
 
1.5%
슬 21
 
1.5%
Other values (299) 1022
71.2%
Uppercase Letter
ValueCountFrequency (%)
P 429
43.7%
C 427
43.5%
E 19
 
1.9%
O 13
 
1.3%
A 13
 
1.3%
X 9
 
0.9%
T 8
 
0.8%
K 7
 
0.7%
N 6
 
0.6%
G 5
 
0.5%
Other values (15) 45
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
e 8
13.3%
n 6
10.0%
o 5
 
8.3%
p 5
 
8.3%
c 5
 
8.3%
a 4
 
6.7%
i 4
 
6.7%
l 4
 
6.7%
s 3
 
5.0%
y 3
 
5.0%
Other values (6) 13
21.7%
Decimal Number
ValueCountFrequency (%)
2 7
26.9%
5 4
15.4%
3 4
15.4%
7 3
11.5%
6 3
11.5%
1 2
 
7.7%
4 1
 
3.8%
9 1
 
3.8%
8 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
; 1
 
25.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1436
55.3%
Latin 1041
40.1%
Common 119
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 125
 
8.7%
이 55
 
3.8%
드 39
 
2.7%
스 38
 
2.6%
점 37
 
2.6%
게 30
 
2.1%
다 27
 
1.9%
롯 21
 
1.5%
랜 21
 
1.5%
슬 21
 
1.5%
Other values (299) 1022
71.2%
Latin
ValueCountFrequency (%)
P 429
41.2%
C 427
41.0%
E 19
 
1.8%
O 13
 
1.2%
A 13
 
1.2%
X 9
 
0.9%
e 8
 
0.8%
T 8
 
0.8%
K 7
 
0.7%
N 6
 
0.6%
Other values (31) 102
 
9.8%
Common
ValueCountFrequency (%)
85
71.4%
2 7
 
5.9%
5 4
 
3.4%
3 4
 
3.4%
7 3
 
2.5%
6 3
 
2.5%
. 3
 
2.5%
1 2
 
1.7%
( 2
 
1.7%
) 2
 
1.7%
Other values (4) 4
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1436
55.3%
ASCII 1160
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 429
37.0%
C 427
36.8%
85
 
7.3%
E 19
 
1.6%
O 13
 
1.1%
A 13
 
1.1%
X 9
 
0.8%
e 8
 
0.7%
T 8
 
0.7%
2 7
 
0.6%
Other values (45) 142
 
12.2%
Hangul
ValueCountFrequency (%)
방 125
 
8.7%
이 55
 
3.8%
드 39
 
2.7%
스 38
 
2.6%
점 37
 
2.6%
게 30
 
2.1%
다 27
 
1.9%
롯 21
 
1.5%
랜 21
 
1.5%
슬 21
 
1.5%
Other values (299) 1022
71.2%

영업소소재지(도로명)
Text

Distinct449
Distinct (%)99.1%
Missing1
Missing (%)0.2%
Memory size3.7 KiB
2023-12-13T04:59:00.468246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length30.046358
Min length20

Characters and Unicode

Total characters13611
Distinct characters187
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

Unique445 ?
Unique (%)98.2%

Sample

1st row경상북도 구미시 선산읍 남문로3길 16
2nd row경상북도 구미시 사곡로 23, 2층 (사곡동)
3rd row경상북도 구미시 인동35길 15, 1층 (인의동)
4th row경상북도 구미시 왕산로3길 36 (임은동)
5th row경상북도 구미시 인동20길 17-2 (진평동)
ValueCountFrequency (%)
경상북도 453
 
15.7%
구미시 453
 
15.7%
1층 296
 
10.3%
원평동 105
 
3.6%
진평동 61
 
2.1%
2층 46
 
1.6%
봉곡동 39
 
1.4%
인의동 38
 
1.3%
사곡동 33
 
1.1%
옥계동 33
 
1.1%
Other values (550) 1323
45.9%
2023-12-13T04:59:00.979797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2427
 
17.8%
1 775
 
5.7%
동 583
 
4.3%
상 528
 
3.9%
시 501
 
3.7%
구 499
 
3.7%
미 495
 
3.6%
북 470
 
3.5%
도 470
 
3.5%
경 453
 
3.3%
Other values (177) 6410
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7592
55.8%
Space Separator 2427
 
17.8%
Decimal Number 2187
 
16.1%
Other Punctuation 436
 
3.2%
Close Punctuation 410
 
3.0%
Open Punctuation 410
 
3.0%
Dash Punctuation 141
 
1.0%
Uppercase Letter 5
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 583
 
7.7%
상 528
 
7.0%
시 501
 
6.6%
구 499
 
6.6%
미 495
 
6.5%
북 470
 
6.2%
도 470
 
6.2%
경 453
 
6.0%
층 371
 
4.9%
로 357
 
4.7%
Other values (157) 2865
37.7%
Decimal Number
ValueCountFrequency (%)
1 775
35.4%
2 348
15.9%
3 208
 
9.5%
5 150
 
6.9%
4 138
 
6.3%
6 138
 
6.3%
0 136
 
6.2%
8 113
 
5.2%
9 94
 
4.3%
7 87
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
A 1
20.0%
M 1
20.0%
K 1
20.0%
Space Separator
ValueCountFrequency (%)
2427
100.0%
Other Punctuation
ValueCountFrequency (%)
, 436
100.0%
Close Punctuation
ValueCountFrequency (%)
) 410
100.0%
Open Punctuation
ValueCountFrequency (%)
( 410
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7592
55.8%
Common 6014
44.2%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 583
 
7.7%
상 528
 
7.0%
시 501
 
6.6%
구 499
 
6.6%
미 495
 
6.5%
북 470
 
6.2%
도 470
 
6.2%
경 453
 
6.0%
층 371
 
4.9%
로 357
 
4.7%
Other values (157) 2865
37.7%
Common
ValueCountFrequency (%)
2427
40.4%
1 775
 
12.9%
, 436
 
7.2%
) 410
 
6.8%
( 410
 
6.8%
2 348
 
5.8%
3 208
 
3.5%
5 150
 
2.5%
- 141
 
2.3%
4 138
 
2.3%
Other values (6) 571
 
9.5%
Latin
ValueCountFrequency (%)
B 2
40.0%
A 1
20.0%
M 1
20.0%
K 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7592
55.8%
ASCII 6019
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2427
40.3%
1 775
 
12.9%
, 436
 
7.2%
) 410
 
6.8%
( 410
 
6.8%
2 348
 
5.8%
3 208
 
3.5%
5 150
 
2.5%
- 141
 
2.3%
4 138
 
2.3%
Other values (10) 576
 
9.6%
Hangul
ValueCountFrequency (%)
동 583
 
7.7%
상 528
 
7.0%
시 501
 
6.6%
구 499
 
6.6%
미 495
 
6.5%
북 470
 
6.2%
도 470
 
6.2%
경 453
 
6.0%
층 371
 
4.9%
로 357
 
4.7%
Other values (157) 2865
37.7%

영업소소재지(지번)
Text

Distinct424
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-13T04:59:01.342825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length20.603524
Min length16

Characters and Unicode

Total characters9354
Distinct characters145
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique398 ?
Unique (%)87.7%

Sample

1st row경상북도 구미시 선산읍 완전리 188
2nd row경상북도 구미시 사곡동 685-8
3rd row경상북도 구미시 인의동 997-5 1층
4th row경상북도 구미시 임은동 521
5th row경상북도 구미시 진평동 27-1
ValueCountFrequency (%)
경상북도 454
23.1%
구미시 454
23.1%
원평동 105
 
5.3%
진평동 61
 
3.1%
봉곡동 39
 
2.0%
인의동 38
 
1.9%
옥계동 33
 
1.7%
사곡동 33
 
1.7%
산동읍 19
 
1.0%
황상동 17
 
0.9%
Other values (504) 716
36.4%
2023-12-13T04:59:01.780147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1950
20.8%
상 490
 
5.2%
도 468
 
5.0%
시 462
 
4.9%
구 460
 
4.9%
미 456
 
4.9%
경 454
 
4.9%
북 454
 
4.9%
동 436
 
4.7%
1 407
 
4.4%
Other values (135) 3317
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4958
53.0%
Decimal Number 2041
21.8%
Space Separator 1950
 
20.8%
Dash Punctuation 394
 
4.2%
Other Punctuation 7
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 490
9.9%
도 468
9.4%
시 462
9.3%
구 460
9.3%
미 456
9.2%
경 454
9.2%
북 454
9.2%
동 436
8.8%
평 182
 
3.7%
원 116
 
2.3%
Other values (117) 980
19.8%
Decimal Number
ValueCountFrequency (%)
1 407
19.9%
2 290
14.2%
3 217
10.6%
0 204
10.0%
4 199
9.8%
5 165
8.1%
6 158
 
7.7%
7 149
 
7.3%
8 143
 
7.0%
9 109
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
B 1
25.0%
M 1
25.0%
K 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
/ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1950
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 394
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4958
53.0%
Common 4392
47.0%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 490
9.9%
도 468
9.4%
시 462
9.3%
구 460
9.3%
미 456
9.2%
경 454
9.2%
북 454
9.2%
동 436
8.8%
평 182
 
3.7%
원 116
 
2.3%
Other values (117) 980
19.8%
Common
ValueCountFrequency (%)
1950
44.4%
1 407
 
9.3%
- 394
 
9.0%
2 290
 
6.6%
3 217
 
4.9%
0 204
 
4.6%
4 199
 
4.5%
5 165
 
3.8%
6 158
 
3.6%
7 149
 
3.4%
Other values (4) 259
 
5.9%
Latin
ValueCountFrequency (%)
A 1
25.0%
B 1
25.0%
M 1
25.0%
K 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4958
53.0%
ASCII 4396
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1950
44.4%
1 407
 
9.3%
- 394
 
9.0%
2 290
 
6.6%
3 217
 
4.9%
0 204
 
4.6%
4 199
 
4.5%
5 165
 
3.8%
6 158
 
3.6%
7 149
 
3.4%
Other values (8) 263
 
6.0%
Hangul
ValueCountFrequency (%)
상 490
9.9%
도 468
9.4%
시 462
9.3%
구 460
9.3%
미 456
9.2%
경 454
9.2%
북 454
9.2%
동 436
8.8%
평 182
 
3.7%
원 116
 
2.3%
Other values (117) 980
19.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2023-06-23 00:00:00
Maximum2023-06-23 00:00:00
2023-12-13T04:59:01.870579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:59:01.943593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T04:58:58.570025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T04:58:58.715321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:58:58.869614image/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

연번상호영업소소재지(도로명)영업소소재지(지번)데이터기준일자
01PC BOX경상북도 구미시 선산읍 남문로3길 16경상북도 구미시 선산읍 완전리 1882023-06-23
12이게PC방이다 사곡점경상북도 구미시 사곡로 23, 2층 (사곡동)경상북도 구미시 사곡동 685-82023-06-23
23EX PC경상북도 구미시 인동35길 15, 1층 (인의동)경상북도 구미시 인의동 997-5 1층2023-06-23
34이게PC방이다 임은점경상북도 구미시 왕산로3길 36 (임은동)경상북도 구미시 임은동 5212023-06-23
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