Overview

Dataset statistics

Number of variables8
Number of observations1257
Missing cells3156
Missing cells (%)31.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.9 KiB
Average record size in memory65.1 B

Variable types

Numeric1
Text6
Categorical1

Dataset

Description순번,회사명,대표자,주소,호실,서비스,홈페이지,연락처
Author서울산업진흥원
URLhttps://data.seoul.go.kr/dataList/OA-2693/S/1/datasetView.do

Alerts

순번 is highly overall correlated with 주소High correlation
주소 is highly overall correlated with 순번High correlation
대표자 has 454 (36.1%) missing valuesMissing
호실 has 938 (74.6%) missing valuesMissing
서비스 has 37 (2.9%) missing valuesMissing
홈페이지 has 947 (75.3%) missing valuesMissing
연락처 has 780 (62.1%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 11:27:17.357370
Analysis finished2024-04-06 11:27:19.265610
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1257
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean629.06523
Minimum1
Maximum1259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-06T20:27:19.389431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63.8
Q1315
median629
Q3943
95-th percentile1194.2
Maximum1259
Range1258
Interquartile range (IQR)628

Descriptive statistics

Standard deviation363.11846
Coefficient of variation (CV)0.57723498
Kurtosis-1.1987671
Mean629.06523
Median Absolute Deviation (MAD)314
Skewness0.00098035303
Sum790735
Variance131855.01
MonotonicityStrictly decreasing
2024-04-06T20:27:19.680748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1259 1
 
0.1%
422 1
 
0.1%
415 1
 
0.1%
416 1
 
0.1%
417 1
 
0.1%
418 1
 
0.1%
419 1
 
0.1%
420 1
 
0.1%
421 1
 
0.1%
423 1
 
0.1%
Other values (1247) 1247
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1259 1
0.1%
1258 1
0.1%
1257 1
0.1%
1256 1
0.1%
1255 1
0.1%
1254 1
0.1%
1253 1
0.1%
1252 1
0.1%
1251 1
0.1%
1250 1
0.1%

회사명
Text

Distinct1023
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2024-04-06T20:27:20.306273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length6.0461416
Min length2

Characters and Unicode

Total characters7600
Distinct characters626
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique921 ?
Unique (%)73.3%

Sample

1st row지엠홀딩스
2nd row비비드모짜르트
3rd row투썸플레이스팬택점
4th row더컵
5th row파니모르
ValueCountFrequency (%)
cj 28
 
2.1%
팬택 23
 
1.7%
e&m 22
 
1.6%
한솔교육 16
 
1.2%
중소기업중앙회 15
 
1.1%
sbs 14
 
1.0%
kbs미디어 11
 
0.8%
sbs플러스 9
 
0.7%
해양수산개발원 6
 
0.4%
cgv 6
 
0.4%
Other values (1046) 1189
88.8%
2024-04-06T20:27:21.151529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 310
 
4.1%
이 238
 
3.1%
리 159
 
2.1%
S 128
 
1.7%
점 124
 
1.6%
아 117
 
1.5%
디 111
 
1.5%
C 108
 
1.4%
B 101
 
1.3%
한 94
 
1.2%
Other values (616) 6110
80.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6522
85.8%
Uppercase Letter 755
 
9.9%
Lowercase Letter 118
 
1.6%
Space Separator 82
 
1.1%
Other Punctuation 37
 
0.5%
Decimal Number 29
 
0.4%
Close Punctuation 24
 
0.3%
Open Punctuation 24
 
0.3%
Connector Punctuation 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 310
 
4.8%
이 238
 
3.6%
리 159
 
2.4%
점 124
 
1.9%
아 117
 
1.8%
디 111
 
1.7%
한 94
 
1.4%
에 89
 
1.4%
트 86
 
1.3%
국 84
 
1.3%
Other values (550) 5110
78.4%
Uppercase Letter
ValueCountFrequency (%)
S 128
17.0%
C 108
14.3%
B 101
13.4%
M 75
9.9%
J 47
 
6.2%
K 40
 
5.3%
D 36
 
4.8%
E 30
 
4.0%
T 29
 
3.8%
G 26
 
3.4%
Other values (15) 135
17.9%
Lowercase Letter
ValueCountFrequency (%)
a 12
10.2%
o 12
10.2%
e 11
 
9.3%
i 10
 
8.5%
r 10
 
8.5%
t 8
 
6.8%
n 8
 
6.8%
p 6
 
5.1%
m 6
 
5.1%
c 6
 
5.1%
Other values (11) 29
24.6%
Decimal Number
ValueCountFrequency (%)
2 6
20.7%
0 6
20.7%
5 5
17.2%
4 4
13.8%
1 2
 
6.9%
9 2
 
6.9%
3 2
 
6.9%
7 1
 
3.4%
8 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
& 27
73.0%
. 9
 
24.3%
, 1
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 22
91.7%
] 2
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 22
91.7%
[ 2
 
8.3%
Space Separator
ValueCountFrequency (%)
82
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6522
85.8%
Latin 873
 
11.5%
Common 205
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 310
 
4.8%
이 238
 
3.6%
리 159
 
2.4%
점 124
 
1.9%
아 117
 
1.8%
디 111
 
1.7%
한 94
 
1.4%
에 89
 
1.4%
트 86
 
1.3%
국 84
 
1.3%
Other values (550) 5110
78.4%
Latin
ValueCountFrequency (%)
S 128
14.7%
C 108
12.4%
B 101
 
11.6%
M 75
 
8.6%
J 47
 
5.4%
K 40
 
4.6%
D 36
 
4.1%
E 30
 
3.4%
T 29
 
3.3%
G 26
 
3.0%
Other values (36) 253
29.0%
Common
ValueCountFrequency (%)
82
40.0%
& 27
 
13.2%
) 22
 
10.7%
( 22
 
10.7%
. 9
 
4.4%
_ 7
 
3.4%
2 6
 
2.9%
0 6
 
2.9%
5 5
 
2.4%
4 4
 
2.0%
Other values (10) 15
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6522
85.8%
ASCII 1078
 
14.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 310
 
4.8%
이 238
 
3.6%
리 159
 
2.4%
점 124
 
1.9%
아 117
 
1.8%
디 111
 
1.7%
한 94
 
1.4%
에 89
 
1.4%
트 86
 
1.3%
국 84
 
1.3%
Other values (550) 5110
78.4%
ASCII
ValueCountFrequency (%)
S 128
 
11.9%
C 108
 
10.0%
B 101
 
9.4%
82
 
7.6%
M 75
 
7.0%
J 47
 
4.4%
K 40
 
3.7%
D 36
 
3.3%
E 30
 
2.8%
T 29
 
2.7%
Other values (56) 402
37.3%

대표자
Text

MISSING 

Distinct594
Distinct (%)74.0%
Missing454
Missing (%)36.1%
Memory size9.9 KiB
2024-04-06T20:27:21.778438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.2590286
Min length1

Characters and Unicode

Total characters2617
Distinct characters258
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

Unique516 ?
Unique (%)64.3%

Sample

1st row김지훈
2nd row장여진
3rd row김일천
4th row김재은
5th row최재훈
ValueCountFrequency (%)
박병엽 23
 
2.8%
하대중 20
 
2.4%
변재용 16
 
1.9%
김기문 15
 
1.8%
우원길 14
 
1.7%
금동수 10
 
1.2%
홍성완,박종 9
 
1.1%
정경원 6
 
0.7%
김학소 6
 
0.7%
김진수외2인 6
 
0.7%
Other values (602) 699
84.8%
2024-04-06T20:27:22.604833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 156
 
6.0%
이 118
 
4.5%
박 78
 
3.0%
정 75
 
2.9%
영 57
 
2.2%
수 56
 
2.1%
성 55
 
2.1%
재 47
 
1.8%
희 43
 
1.6%
기 43
 
1.6%
Other values (248) 1889
72.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2520
96.3%
Uppercase Letter 39
 
1.5%
Space Separator 21
 
0.8%
Other Punctuation 18
 
0.7%
Decimal Number 11
 
0.4%
Lowercase Letter 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 156
 
6.2%
이 118
 
4.7%
박 78
 
3.1%
정 75
 
3.0%
영 57
 
2.3%
수 56
 
2.2%
성 55
 
2.2%
재 47
 
1.9%
희 43
 
1.7%
기 43
 
1.7%
Other values (220) 1792
71.1%
Uppercase Letter
ValueCountFrequency (%)
A 6
15.4%
E 5
12.8%
L 4
10.3%
M 3
 
7.7%
K 3
 
7.7%
I 2
 
5.1%
O 2
 
5.1%
H 2
 
5.1%
D 2
 
5.1%
R 2
 
5.1%
Other values (7) 8
20.5%
Lowercase Letter
ValueCountFrequency (%)
n 2
25.0%
g 2
25.0%
m 1
12.5%
i 1
12.5%
o 1
12.5%
k 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 16
88.9%
/ 2
 
11.1%
Decimal Number
ValueCountFrequency (%)
2 6
54.5%
1 5
45.5%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2520
96.3%
Common 50
 
1.9%
Latin 47
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 156
 
6.2%
이 118
 
4.7%
박 78
 
3.1%
정 75
 
3.0%
영 57
 
2.3%
수 56
 
2.2%
성 55
 
2.2%
재 47
 
1.9%
희 43
 
1.7%
기 43
 
1.7%
Other values (220) 1792
71.1%
Latin
ValueCountFrequency (%)
A 6
 
12.8%
E 5
 
10.6%
L 4
 
8.5%
M 3
 
6.4%
K 3
 
6.4%
I 2
 
4.3%
O 2
 
4.3%
H 2
 
4.3%
D 2
 
4.3%
R 2
 
4.3%
Other values (13) 16
34.0%
Common
ValueCountFrequency (%)
21
42.0%
, 16
32.0%
2 6
 
12.0%
1 5
 
10.0%
/ 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2520
96.3%
ASCII 97
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 156
 
6.2%
이 118
 
4.7%
박 78
 
3.1%
정 75
 
3.0%
영 57
 
2.3%
수 56
 
2.2%
성 55
 
2.2%
재 47
 
1.9%
희 43
 
1.7%
기 43
 
1.7%
Other values (220) 1792
71.1%
ASCII
ValueCountFrequency (%)
21
21.6%
, 16
16.5%
2 6
 
6.2%
A 6
 
6.2%
E 5
 
5.2%
1 5
 
5.2%
L 4
 
4.1%
M 3
 
3.1%
K 3
 
3.1%
I 2
 
2.1%
Other values (18) 26
26.8%

주소
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
서울 마포구 월드컵북로 402
173 
서울 마포구 월드컵북로 396
150 
서울 마포구 성암로 330
124 
서울특별시 마포구 상암동 1622
76 
서울 마포구 성암로 189
 
65
Other values (35)
669 

Length

Max length22
Median length21
Mean length15.86078
Min length4

Unique

Unique6 ?
Unique (%)0.5%

Sample

1st row서울특별시 마포구 상암동 1649
2nd row서울특별시 마포구 상암동 1601
3rd row서울특별시 마포구 상암동 1623
4th row서울특별시 마포구 상암동 1601
5th row서울특별시 마포구 상암동 1601

Common Values

ValueCountFrequency (%)
서울 마포구 월드컵북로 402 173
 
13.8%
서울 마포구 월드컵북로 396 150
 
11.9%
서울 마포구 성암로 330 124
 
9.9%
서울특별시 마포구 상암동 1622 76
 
6.0%
서울 마포구 성암로 189 65
 
5.2%
서울특별시 마포구 상암동 1605 52
 
4.1%
서울 마포구 월드컵북로 434 50
 
4.0%
서울특별시 마포구 상암동 1652 42
 
3.3%
서울 마포구 상암산로 76 40
 
3.2%
서울특별시 마포구 상암동 1606 36
 
2.9%
Other values (30) 449
35.7%

Length

2024-04-06T20:27:22.892484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마포구 1245
24.9%
서울 937
18.8%
월드컵북로 417
 
8.4%
서울특별시 308
 
6.2%
상암동 277
 
5.5%
성암로 252
 
5.0%
402 173
 
3.5%
396 150
 
3.0%
330 124
 
2.5%
상암산로 122
 
2.4%
Other values (42) 987
19.8%

호실
Text

MISSING 

Distinct176
Distinct (%)55.2%
Missing938
Missing (%)74.6%
Memory size9.9 KiB
2024-04-06T20:27:23.379611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.3416928
Min length1

Characters and Unicode

Total characters1066
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)40.8%

Sample

1st row1302
2nd row1053
3rd row101
4th row1011
5th row1005
ValueCountFrequency (%)
1 23
 
7.2%
101 10
 
3.1%
301 8
 
2.5%
401 7
 
2.2%
103 7
 
2.2%
102 7
 
2.2%
501 7
 
2.2%
201 6
 
1.9%
104 6
 
1.9%
1601 5
 
1.6%
Other values (166) 233
73.0%
2024-04-06T20:27:24.064625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 391
36.7%
0 263
24.7%
2 94
 
8.8%
5 55
 
5.2%
3 54
 
5.1%
6 49
 
4.6%
4 43
 
4.0%
7 41
 
3.8%
8 37
 
3.5%
9 32
 
3.0%
Other values (2) 7
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1059
99.3%
Dash Punctuation 5
 
0.5%
Other Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 391
36.9%
0 263
24.8%
2 94
 
8.9%
5 55
 
5.2%
3 54
 
5.1%
6 49
 
4.6%
4 43
 
4.1%
7 41
 
3.9%
8 37
 
3.5%
9 32
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1066
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 391
36.7%
0 263
24.7%
2 94
 
8.8%
5 55
 
5.2%
3 54
 
5.1%
6 49
 
4.6%
4 43
 
4.0%
7 41
 
3.8%
8 37
 
3.5%
9 32
 
3.0%
Other values (2) 7
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 391
36.7%
0 263
24.7%
2 94
 
8.8%
5 55
 
5.2%
3 54
 
5.1%
6 49
 
4.6%
4 43
 
4.0%
7 41
 
3.8%
8 37
 
3.5%
9 32
 
3.0%
Other values (2) 7
 
0.7%

서비스
Text

MISSING 

Distinct478
Distinct (%)39.2%
Missing37
Missing (%)2.9%
Memory size9.9 KiB
2024-04-06T20:27:24.446077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length3.7540984
Min length1

Characters and Unicode

Total characters4580
Distinct characters377
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

Unique343 ?
Unique (%)28.1%

Sample

1st row바이오개발
2nd row커피
3rd row커피
4th row국수
5th row커피
ValueCountFrequency (%)
방송 92
 
6.9%
음식 80
 
6.0%
디자인 55
 
4.1%
sw개발 38
 
2.8%
sw 38
 
2.8%
커피 30
 
2.2%
편의점 23
 
1.7%
커피숍 22
 
1.6%
it 21
 
1.6%
한식 19
 
1.4%
Other values (494) 917
68.7%
2024-04-06T20:27:25.011580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
방 146
 
3.2%
송 145
 
3.2%
식 138
 
3.0%
115
 
2.5%
자 100
 
2.2%
인 100
 
2.2%
S 100
 
2.2%
음 97
 
2.1%
W 92
 
2.0%
제 84
 
1.8%
Other values (367) 3463
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4036
88.1%
Uppercase Letter 351
 
7.7%
Space Separator 115
 
2.5%
Other Punctuation 42
 
0.9%
Lowercase Letter 34
 
0.7%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 146
 
3.6%
송 145
 
3.6%
식 138
 
3.4%
자 100
 
2.5%
인 100
 
2.5%
음 97
 
2.4%
제 84
 
2.1%
디 81
 
2.0%
스 64
 
1.6%
개 62
 
1.5%
Other values (328) 3019
74.8%
Uppercase Letter
ValueCountFrequency (%)
S 100
28.5%
W 92
26.2%
I 36
 
10.3%
T 36
 
10.3%
D 14
 
4.0%
B 13
 
3.7%
M 12
 
3.4%
C 9
 
2.6%
P 7
 
2.0%
N 6
 
1.7%
Other values (11) 26
 
7.4%
Lowercase Letter
ValueCountFrequency (%)
k 6
17.6%
e 6
17.6%
n 5
14.7%
o 4
11.8%
c 2
 
5.9%
i 2
 
5.9%
g 2
 
5.9%
a 2
 
5.9%
y 2
 
5.9%
r 1
 
2.9%
Other values (2) 2
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 32
76.2%
/ 7
 
16.7%
& 2
 
4.8%
. 1
 
2.4%
Space Separator
ValueCountFrequency (%)
115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4036
88.1%
Latin 385
 
8.4%
Common 159
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 146
 
3.6%
송 145
 
3.6%
식 138
 
3.4%
자 100
 
2.5%
인 100
 
2.5%
음 97
 
2.4%
제 84
 
2.1%
디 81
 
2.0%
스 64
 
1.6%
개 62
 
1.5%
Other values (328) 3019
74.8%
Latin
ValueCountFrequency (%)
S 100
26.0%
W 92
23.9%
I 36
 
9.4%
T 36
 
9.4%
D 14
 
3.6%
B 13
 
3.4%
M 12
 
3.1%
C 9
 
2.3%
P 7
 
1.8%
k 6
 
1.6%
Other values (23) 60
15.6%
Common
ValueCountFrequency (%)
115
72.3%
, 32
 
20.1%
/ 7
 
4.4%
- 2
 
1.3%
& 2
 
1.3%
. 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4036
88.1%
ASCII 544
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
방 146
 
3.6%
송 145
 
3.6%
식 138
 
3.4%
자 100
 
2.5%
인 100
 
2.5%
음 97
 
2.4%
제 84
 
2.1%
디 81
 
2.0%
스 64
 
1.6%
개 62
 
1.5%
Other values (328) 3019
74.8%
ASCII
ValueCountFrequency (%)
115
21.1%
S 100
18.4%
W 92
16.9%
I 36
 
6.6%
T 36
 
6.6%
, 32
 
5.9%
D 14
 
2.6%
B 13
 
2.4%
M 12
 
2.2%
C 9
 
1.7%
Other values (29) 85
15.6%

홈페이지
Text

MISSING 

Distinct165
Distinct (%)53.2%
Missing947
Missing (%)75.3%
Memory size9.9 KiB
2024-04-06T20:27:25.346088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length16.129032
Min length1

Characters and Unicode

Total characters5000
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)42.3%

Sample

1st rowwww.LuxenTech.com
2nd rowwww.kocca.kr
3rd rowwww.eduhansol.co.kr
4th rowwww.cjenm.com
5th rowwww.eduhansol.co.kr
ValueCountFrequency (%)
www.pantech.com 23
 
7.4%
www.cjenm.com 21
 
6.8%
www.eduhansol.co.kr 16
 
5.2%
www.kbiz.or.kr 15
 
4.8%
www.sbs.co.kr 14
 
4.5%
www.kbsmedia.co.kr 11
 
3.5%
http://sbsplus.sbs.co.kr 9
 
2.9%
www.nipa.or.kr 6
 
1.9%
www.kmi.re.kr 6
 
1.9%
www.kbsn.co.kr 5
 
1.6%
Other values (155) 184
59.4%
2024-04-06T20:27:25.923421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 901
18.0%
. 767
15.3%
o 421
 
8.4%
c 358
 
7.2%
r 262
 
5.2%
k 251
 
5.0%
m 235
 
4.7%
e 208
 
4.2%
s 198
 
4.0%
n 187
 
3.7%
Other values (28) 1212
24.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4154
83.1%
Other Punctuation 825
 
16.5%
Dash Punctuation 7
 
0.1%
Decimal Number 7
 
0.1%
Uppercase Letter 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 901
21.7%
o 421
10.1%
c 358
 
8.6%
r 262
 
6.3%
k 251
 
6.0%
m 235
 
5.7%
e 208
 
5.0%
s 198
 
4.8%
n 187
 
4.5%
a 175
 
4.2%
Other values (15) 958
23.1%
Uppercase Letter
ValueCountFrequency (%)
D 2
28.6%
B 1
14.3%
F 1
14.3%
L 1
14.3%
S 1
14.3%
T 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 767
93.0%
/ 40
 
4.8%
: 18
 
2.2%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
1 2
28.6%
4 1
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4161
83.2%
Common 839
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 901
21.7%
o 421
10.1%
c 358
 
8.6%
r 262
 
6.3%
k 251
 
6.0%
m 235
 
5.6%
e 208
 
5.0%
s 198
 
4.8%
n 187
 
4.5%
a 175
 
4.2%
Other values (21) 965
23.2%
Common
ValueCountFrequency (%)
. 767
91.4%
/ 40
 
4.8%
: 18
 
2.1%
- 7
 
0.8%
2 4
 
0.5%
1 2
 
0.2%
4 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 901
18.0%
. 767
15.3%
o 421
 
8.4%
c 358
 
7.2%
r 262
 
5.2%
k 251
 
5.0%
m 235
 
4.7%
e 208
 
4.2%
s 198
 
4.0%
n 187
 
3.7%
Other values (28) 1212
24.2%

연락처
Text

MISSING 

Distinct331
Distinct (%)69.4%
Missing780
Missing (%)62.1%
Memory size9.9 KiB
2024-04-06T20:27:26.305962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.268344
Min length1

Characters and Unicode

Total characters4898
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

Unique277 ?
Unique (%)58.1%

Sample

1st row3153-7010
2nd row3153-1426
3rd row1588-1185
4th row1588-1185
5th row1588-1185
ValueCountFrequency (%)
02-2030-2383 23
 
4.8%
1588-1185 16
 
3.4%
02-2124-3114 15
 
3.1%
02-2061-0006 14
 
2.9%
6939-8032 11
 
2.3%
02-2133-6700 9
 
1.9%
2132-1213 6
 
1.3%
2105-2700 6
 
1.3%
787-3333 5
 
1.0%
3704-8400 4
 
0.8%
Other values (321) 368
77.1%
2024-04-06T20:27:26.920336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 854
17.4%
- 728
14.9%
2 648
13.2%
3 647
13.2%
1 426
8.7%
6 332
 
6.8%
5 311
 
6.3%
8 303
 
6.2%
7 278
 
5.7%
9 208
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4170
85.1%
Dash Punctuation 728
 
14.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 854
20.5%
2 648
15.5%
3 647
15.5%
1 426
10.2%
6 332
 
8.0%
5 311
 
7.5%
8 303
 
7.3%
7 278
 
6.7%
9 208
 
5.0%
4 163
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 728
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4898
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 854
17.4%
- 728
14.9%
2 648
13.2%
3 647
13.2%
1 426
8.7%
6 332
 
6.8%
5 311
 
6.3%
8 303
 
6.2%
7 278
 
5.7%
9 208
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4898
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 854
17.4%
- 728
14.9%
2 648
13.2%
3 647
13.2%
1 426
8.7%
6 332
 
6.8%
5 311
 
6.3%
8 303
 
6.2%
7 278
 
5.7%
9 208
 
4.2%

Interactions

2024-04-06T20:27:18.475965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T20:27:27.070024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번주소
순번1.0000.979
주소0.9791.000
2024-04-06T20:27:27.204007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번주소
순번1.0000.837
주소0.8371.000

Missing values

2024-04-06T20:27:18.676867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T20:27:18.909507image/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.
2024-04-06T20:27:19.147233image/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

순번회사명대표자주소호실서비스홈페이지연락처
01259지엠홀딩스김지훈서울특별시 마포구 상암동 16491302바이오개발<NA><NA>
11258비비드모짜르트장여진서울특별시 마포구 상암동 16011053커피<NA><NA>
21257투썸플레이스팬택점김일천서울특별시 마포구 상암동 1623101커피<NA><NA>
31256더컵김재은서울특별시 마포구 상암동 16011011국수<NA><NA>
41255파니모르최재훈서울특별시 마포구 상암동 16011005커피<NA><NA>
51254파니모르최재훈서울특별시 마포구 상암동 16011006커피<NA><NA>
61253안순선법무사사무소안순선서울특별시 마포구 상암동 16013026법무사<NA><NA>
71252티제이웍스<NA>서울특별시 마포구 상암동 1601807영상<NA><NA>
81251엔케이비스타<NA><NA>955SW<NA><NA>
91250잉가솔랜드코리아신영호서울특별시 마포구 상암동 1601954보안솔루션<NA><NA>
순번회사명대표자주소호실서비스홈페이지연락처
124710나인띠모MBC점<NA>서울 마포구 성암로 255<NA>스파게티<NA><NA>
12489크리스탈제이드MBC점<NA>서울 마포구 성암로 255<NA>중식<NA>02-303-0838
12498폴바셋MBC점<NA>서울 마포구 성암로 255<NA>커피www.baristapaulbasset.co.kr02-376-9019
12507설빙MBC점<NA>서울 마포구 성암로 255<NA>아이스크림<NA><NA>
12516매드포갈릭MBC점<NA>서울 마포구 성암로 255<NA>와인&마늘<NA>02-3151-0533
12525보헤미안박이추커피안우정서울 마포구 성암로 255<NA>커피<NA>02-372-6688
12534무스쿠스MBC점<NA>서울 마포구 성암로 255<NA>초밥뷔페<NA>02-376-8000
12543MBC C&I박진석서울 마포구 성암로 255<NA>방송<NA>3219-5814
12552아이엠비씨허연회서울 마포구 성암로 255<NA>방송www.imbc.com02-2105-1100
12561문화방송안광한서울 마포구 성암로 255<NA>방송www.imbc.com02-789-0011