Overview

Dataset statistics

Number of variables4
Number of observations34
Missing cells7
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory36.9 B

Variable types

Numeric1
Text3

Dataset

Description인천광역시 부평구 치과기공소 현황 데이터는 치과기공소명, 소재지(도로명), 기공소 전화번호에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15102679/fileData.do

Alerts

전화번호 has 7 (20.6%) missing valuesMissing
순번 has unique valuesUnique
치과기공소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:33:49.382745
Analysis finished2023-12-12 05:33:50.033070
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.5
Minimum1
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T14:33:50.105475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q19.25
median17.5
Q325.75
95-th percentile32.35
Maximum34
Range33
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation9.9582462
Coefficient of variation (CV)0.56904264
Kurtosis-1.2
Mean17.5
Median Absolute Deviation (MAD)8.5
Skewness0
Sum595
Variance99.166667
MonotonicityStrictly increasing
2023-12-12T14:33:50.310601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 1
 
2.9%
27 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
28 1
 
2.9%
19 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%
25 1
2.9%

치과기공소명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T14:33:50.569146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length8.9411765
Min length4

Characters and Unicode

Total characters304
Distinct characters93
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

Unique34 ?
Unique (%)100.0%

Sample

1st row채움치과기공소
2nd row진치과기공소(Jin Dental Lab)
3rd row에이엠솔루션
4th row뉴에이스치과기공소
5th row로이덴트(Roydent)
ValueCountFrequency (%)
치과기공소 3
 
7.5%
채움치과기공소 1
 
2.5%
lab 1
 
2.5%
참사랑치과기공소 1
 
2.5%
홀인원치과기공소 1
 
2.5%
맑은치과기공소 1
 
2.5%
뉴코리아치과기공소 1
 
2.5%
어울림치과기공소 1
 
2.5%
진치과기공소(jin 1
 
2.5%
dental 1
 
2.5%
Other values (28) 28
70.0%
2023-12-12T14:33:51.314066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 31
 
10.2%
소 31
 
10.2%
치 30
 
9.9%
공 30
 
9.9%
과 29
 
9.5%
이 9
 
3.0%
6
 
2.0%
e 5
 
1.6%
트 5
 
1.6%
덴 4
 
1.3%
Other values (83) 124
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
83.9%
Lowercase Letter 27
 
8.9%
Uppercase Letter 8
 
2.6%
Space Separator 6
 
2.0%
Close Punctuation 4
 
1.3%
Open Punctuation 4
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 31
 
12.2%
소 31
 
12.2%
치 30
 
11.8%
공 30
 
11.8%
과 29
 
11.4%
이 9
 
3.5%
트 5
 
2.0%
덴 4
 
1.6%
리 4
 
1.6%
뉴 3
 
1.2%
Other values (61) 79
31.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
18.5%
n 4
14.8%
i 3
11.1%
t 3
11.1%
h 3
11.1%
a 2
 
7.4%
o 2
 
7.4%
c 1
 
3.7%
b 1
 
3.7%
l 1
 
3.7%
Other values (2) 2
 
7.4%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
H 1
12.5%
J 1
12.5%
D 1
12.5%
L 1
12.5%
R 1
12.5%
W 1
12.5%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
83.9%
Latin 35
 
11.5%
Common 14
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 31
 
12.2%
소 31
 
12.2%
치 30
 
11.8%
공 30
 
11.8%
과 29
 
11.4%
이 9
 
3.5%
트 5
 
2.0%
덴 4
 
1.6%
리 4
 
1.6%
뉴 3
 
1.2%
Other values (61) 79
31.0%
Latin
ValueCountFrequency (%)
e 5
14.3%
n 4
11.4%
i 3
 
8.6%
t 3
 
8.6%
h 3
 
8.6%
a 2
 
5.7%
T 2
 
5.7%
o 2
 
5.7%
H 1
 
2.9%
c 1
 
2.9%
Other values (9) 9
25.7%
Common
ValueCountFrequency (%)
6
42.9%
) 4
28.6%
( 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
83.9%
ASCII 49
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 31
 
12.2%
소 31
 
12.2%
치 30
 
11.8%
공 30
 
11.8%
과 29
 
11.4%
이 9
 
3.5%
트 5
 
2.0%
덴 4
 
1.6%
리 4
 
1.6%
뉴 3
 
1.2%
Other values (61) 79
31.0%
ASCII
ValueCountFrequency (%)
6
12.2%
e 5
 
10.2%
) 4
 
8.2%
n 4
 
8.2%
( 4
 
8.2%
i 3
 
6.1%
t 3
 
6.1%
h 3
 
6.1%
a 2
 
4.1%
T 2
 
4.1%
Other values (12) 13
26.5%

소재지(도로명)
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T14:33:51.666654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39.5
Mean length32.176471
Min length22

Characters and Unicode

Total characters1094
Distinct characters96
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

Unique34 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 동암남로 32, 3층 (십정동)
2nd row인천광역시 부평구 길주로 639, 현대아이프라자 801일부호 (삼산동)
3rd row인천광역시 부평구 부평대로 337, 부평 제이타워3차 지식산업센터 930호 (청천동)
4th row인천광역시 부평구 부평문화로115번길 50, 2층 (부평동)
5th row인천광역시 부평구 부평대로 70, 4층 402호 (부평동)
ValueCountFrequency (%)
인천광역시 34
 
15.2%
부평구 34
 
15.2%
부평동 12
 
5.4%
2층 10
 
4.5%
3층 8
 
3.6%
십정동 5
 
2.2%
갈산동 5
 
2.2%
4층 4
 
1.8%
주부토로 4
 
1.8%
청천동 4
 
1.8%
Other values (81) 103
46.2%
2023-12-12T14:33:52.234477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
 
17.3%
부 63
 
5.8%
평 52
 
4.8%
동 42
 
3.8%
천 42
 
3.8%
인 39
 
3.6%
, 36
 
3.3%
시 36
 
3.3%
광 35
 
3.2%
역 34
 
3.1%
Other values (86) 526
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 627
57.3%
Space Separator 189
 
17.3%
Decimal Number 162
 
14.8%
Other Punctuation 36
 
3.3%
Close Punctuation 34
 
3.1%
Open Punctuation 34
 
3.1%
Uppercase Letter 6
 
0.5%
Dash Punctuation 5
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 63
 
10.0%
평 52
 
8.3%
동 42
 
6.7%
천 42
 
6.7%
인 39
 
6.2%
시 36
 
5.7%
광 35
 
5.6%
역 34
 
5.4%
구 34
 
5.4%
로 34
 
5.4%
Other values (66) 216
34.4%
Decimal Number
ValueCountFrequency (%)
3 29
17.9%
2 26
16.0%
1 24
14.8%
0 15
9.3%
4 15
9.3%
7 13
8.0%
5 12
7.4%
6 11
 
6.8%
8 9
 
5.6%
9 8
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
U 3
50.0%
B 1
 
16.7%
C 1
 
16.7%
A 1
 
16.7%
Space Separator
ValueCountFrequency (%)
189
100.0%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 627
57.3%
Common 461
42.1%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 63
 
10.0%
평 52
 
8.3%
동 42
 
6.7%
천 42
 
6.7%
인 39
 
6.2%
시 36
 
5.7%
광 35
 
5.6%
역 34
 
5.4%
구 34
 
5.4%
로 34
 
5.4%
Other values (66) 216
34.4%
Common
ValueCountFrequency (%)
189
41.0%
, 36
 
7.8%
) 34
 
7.4%
( 34
 
7.4%
3 29
 
6.3%
2 26
 
5.6%
1 24
 
5.2%
0 15
 
3.3%
4 15
 
3.3%
7 13
 
2.8%
Other values (6) 46
 
10.0%
Latin
ValueCountFrequency (%)
U 3
50.0%
B 1
 
16.7%
C 1
 
16.7%
A 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 627
57.3%
ASCII 467
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
40.5%
, 36
 
7.7%
) 34
 
7.3%
( 34
 
7.3%
3 29
 
6.2%
2 26
 
5.6%
1 24
 
5.1%
0 15
 
3.2%
4 15
 
3.2%
7 13
 
2.8%
Other values (10) 52
 
11.1%
Hangul
ValueCountFrequency (%)
부 63
 
10.0%
평 52
 
8.3%
동 42
 
6.7%
천 42
 
6.7%
인 39
 
6.2%
시 36
 
5.7%
광 35
 
5.6%
역 34
 
5.4%
구 34
 
5.4%
로 34
 
5.4%
Other values (66) 216
34.4%

전화번호
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing7
Missing (%)20.6%
Memory size404.0 B
2023-12-12T14:33:52.522546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters324
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

Unique27 ?
Unique (%)100.0%

Sample

1st row032-431-2809
2nd row032-515-2804
3rd row032-433-2835
4th row032-513-2804
5th row032-506-1592
ValueCountFrequency (%)
032-431-2809 1
 
3.7%
032-524-8188 1
 
3.7%
032-528-0211 1
 
3.7%
032-504-2804 1
 
3.7%
032-442-2804 1
 
3.7%
032-528-2801 1
 
3.7%
032-508-2804 1
 
3.7%
032-526-1884 1
 
3.7%
032-330-1941 1
 
3.7%
032-545-2870 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T14:33:52.920056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 61
18.8%
0 55
17.0%
- 54
16.7%
3 37
11.4%
8 31
9.6%
5 29
9.0%
4 22
 
6.8%
1 17
 
5.2%
9 8
 
2.5%
6 5
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
83.3%
Dash Punctuation 54
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 61
22.6%
0 55
20.4%
3 37
13.7%
8 31
11.5%
5 29
10.7%
4 22
 
8.1%
1 17
 
6.3%
9 8
 
3.0%
6 5
 
1.9%
7 5
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 61
18.8%
0 55
17.0%
- 54
16.7%
3 37
11.4%
8 31
9.6%
5 29
9.0%
4 22
 
6.8%
1 17
 
5.2%
9 8
 
2.5%
6 5
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 61
18.8%
0 55
17.0%
- 54
16.7%
3 37
11.4%
8 31
9.6%
5 29
9.0%
4 22
 
6.8%
1 17
 
5.2%
9 8
 
2.5%
6 5
 
1.5%

Interactions

2023-12-12T14:33:49.733973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:33:53.052504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번치과기공소명소재지(도로명)전화번호
순번1.0001.0001.0001.000
치과기공소명1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.000
전화번호1.0001.0001.0001.000

Missing values

2023-12-12T14:33:49.884233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:33:49.994489image/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

순번치과기공소명소재지(도로명)전화번호
01채움치과기공소인천광역시 부평구 동암남로 32, 3층 (십정동)032-431-2809
12진치과기공소(Jin Dental Lab)인천광역시 부평구 길주로 639, 현대아이프라자 801일부호 (삼산동)032-515-2804
23에이엠솔루션인천광역시 부평구 부평대로 337, 부평 제이타워3차 지식산업센터 930호 (청천동)<NA>
34뉴에이스치과기공소인천광역시 부평구 부평문화로115번길 50, 2층 (부평동)032-433-2835
45로이덴트(Roydent)인천광역시 부평구 부평대로 70, 4층 402호 (부평동)<NA>
56디포유치과기공소인천광역시 부평구 길주로585번길 11, 2층 일부호 (갈산동)<NA>
67라이브치과기공소인천광역시 부평구 부평대로 52, 지1층 일부호 (부평동)<NA>
78하이텍 치과기공소인천광역시 부평구 경인로 1082-1, 3층 (부개동)032-513-2804
89나무치과기공소인천광역시 부평구 육동로 31-1, 중성빌딩 (부평동)<NA>
910꿀벌치과기공소인천광역시 부평구 마장로 43 (십정동)032-506-1592
순번치과기공소명소재지(도로명)전화번호
2425예담치과기공소인천광역시 부평구 화랑북로 6-2, 2층 (산곡동)032-512-2804
2526디자인치과기공소인천광역시 부평구 마장로 438, 3층 (청천동)032-545-2870
2627청화치과기공소인천광역시 부평구 평천로153번길 13, 208호 (청천동, 광명아파트)<NA>
2728어울림치과기공소인천광역시 부평구 장제로75번길 3, 2층 (부평동)032-330-1941
2829뉴코리아치과기공소인천광역시 부평구 시장로 76, 3층 (부평동)032-526-1884
2930맑은치과기공소인천광역시 부평구 길주로547번길 8-16, 3층 (갈산동)032-508-2804
3031홀인원치과기공소인천광역시 부평구 마장로460번길 8, 4층 (청천동)032-528-2801
3132참사랑치과기공소인천광역시 부평구 마장로72번길 4, 2층 (십정동)032-442-2804
3233인천치과기공소인천광역시 부평구 경원대로1347번길 9, 3층 (부평동)032-504-2804
3334심미치과기공소인천광역시 부평구 마장로 287, 2층 (산곡동)032-503-2890