Overview

Dataset statistics

Number of variables11
Number of observations180
Missing cells95
Missing cells (%)4.8%
Duplicate rows1
Duplicate rows (%)0.6%
Total size in memory16.3 KiB
Average record size in memory92.7 B

Variable types

Text6
Categorical1
Numeric4

Dataset

Description김해시 특정고압가스업 현황 (사업장명,영업상태,전화번호,주소,위도 및 경도,사용목적,사용방법,월사용량,수용정원수)
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15084887/fileData.do

Alerts

Dataset has 1 (0.6%) duplicate rowsDuplicates
전화번호 has 68 (37.8%) missing valuesMissing
지번주소 has 5 (2.8%) missing valuesMissing
사용방법 has 19 (10.6%) missing valuesMissing
월사용량 has 14 (7.8%) zerosZeros
수용정원수 has 19 (10.6%) zerosZeros

Reproduction

Analysis started2023-12-12 15:23:59.786144
Analysis finished2023-12-12 15:24:03.638457
Duration3.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct159
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T00:24:03.874351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length7.6555556
Min length2

Characters and Unicode

Total characters1378
Distinct characters194
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

Unique145 ?
Unique (%)80.6%

Sample

1st row(주)풍성정밀관
2nd row하이에어코리아(주)
3rd row홍경에이치엔티
4th row대동브레이징
5th row하이에어코리아(주)
ValueCountFrequency (%)
주)풍성정밀관 5
 
2.4%
의료법인 4
 
2.0%
주)경용중공업 4
 
2.0%
주)한국에스티에스 3
 
1.5%
주식회사 3
 
1.5%
주)유넥스 3
 
1.5%
강일병원 3
 
1.5%
하이에어코리아(주 3
 
1.5%
진영열처리 2
 
1.0%
김해복음병원 2
 
1.0%
Other values (165) 173
84.4%
2023-12-13T00:24:04.283638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 119
 
8.6%
( 116
 
8.4%
) 116
 
8.4%
스 39
 
2.8%
이 36
 
2.6%
원 34
 
2.5%
에 33
 
2.4%
25
 
1.8%
리 23
 
1.7%
성 22
 
1.6%
Other values (184) 815
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1095
79.5%
Open Punctuation 116
 
8.4%
Close Punctuation 116
 
8.4%
Space Separator 25
 
1.8%
Uppercase Letter 13
 
0.9%
Other Punctuation 5
 
0.4%
Decimal Number 4
 
0.3%
Dash Punctuation 2
 
0.1%
Lowercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 119
 
10.9%
스 39
 
3.6%
이 36
 
3.3%
원 34
 
3.1%
에 33
 
3.0%
리 23
 
2.1%
성 22
 
2.0%
병 20
 
1.8%
처 18
 
1.6%
열 18
 
1.6%
Other values (168) 733
66.9%
Uppercase Letter
ValueCountFrequency (%)
H 5
38.5%
D 3
23.1%
I 2
 
15.4%
E 1
 
7.7%
N 1
 
7.7%
G 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
4 1
25.0%
6 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Math Symbol
ValueCountFrequency (%)
< 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1095
79.5%
Common 269
 
19.5%
Latin 14
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 119
 
10.9%
스 39
 
3.6%
이 36
 
3.3%
원 34
 
3.1%
에 33
 
3.0%
리 23
 
2.1%
성 22
 
2.0%
병 20
 
1.8%
처 18
 
1.6%
열 18
 
1.6%
Other values (168) 733
66.9%
Common
ValueCountFrequency (%)
( 116
43.1%
) 116
43.1%
25
 
9.3%
. 5
 
1.9%
- 2
 
0.7%
3 2
 
0.7%
< 1
 
0.4%
4 1
 
0.4%
6 1
 
0.4%
Latin
ValueCountFrequency (%)
H 5
35.7%
D 3
21.4%
I 2
 
14.3%
e 1
 
7.1%
E 1
 
7.1%
N 1
 
7.1%
G 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1095
79.5%
ASCII 283
 
20.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 119
 
10.9%
스 39
 
3.6%
이 36
 
3.3%
원 34
 
3.1%
에 33
 
3.0%
리 23
 
2.1%
성 22
 
2.0%
병 20
 
1.8%
처 18
 
1.6%
열 18
 
1.6%
Other values (168) 733
66.9%
ASCII
ValueCountFrequency (%)
( 116
41.0%
) 116
41.0%
25
 
8.8%
. 5
 
1.8%
H 5
 
1.8%
D 3
 
1.1%
- 2
 
0.7%
3 2
 
0.7%
I 2
 
0.7%
e 1
 
0.4%
Other values (6) 6
 
2.1%

영업상태명
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
휴업
114 
영업
53 
폐업
13 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴업 114
63.3%
영업 53
29.4%
폐업 13
 
7.2%

Length

2023-12-13T00:24:04.425173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:24:04.527651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴업 114
63.3%
영업 53
29.4%
폐업 13
 
7.2%

전화번호
Text

MISSING 

Distinct100
Distinct (%)89.3%
Missing68
Missing (%)37.8%
Memory size1.5 KiB
2023-12-13T00:24:04.758950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.973214
Min length9

Characters and Unicode

Total characters1341
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

Unique90 ?
Unique (%)80.4%

Sample

1st row055-329-3911
2nd row055-330-4000
3rd row055-321-0114
4th row055-330-8888
5th row055-346-0805
ValueCountFrequency (%)
055-338-8245 3
 
2.7%
055-322-9111 3
 
2.7%
055-329-0837 2
 
1.8%
055-326-4243 2
 
1.8%
055-343-3421 2
 
1.8%
055-330-8888 2
 
1.8%
055-310-9100 2
 
1.8%
055-345-6712 2
 
1.8%
055-822-0100 2
 
1.8%
055-313-2197 2
 
1.8%
Other values (90) 90
80.4%
2023-12-13T00:24:05.149377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 272
20.3%
- 223
16.6%
0 211
15.7%
3 191
14.2%
4 88
 
6.6%
2 82
 
6.1%
1 78
 
5.8%
8 60
 
4.5%
7 53
 
4.0%
6 43
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1118
83.4%
Dash Punctuation 223
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 272
24.3%
0 211
18.9%
3 191
17.1%
4 88
 
7.9%
2 82
 
7.3%
1 78
 
7.0%
8 60
 
5.4%
7 53
 
4.7%
6 43
 
3.8%
9 40
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 223
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1341
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 272
20.3%
- 223
16.6%
0 211
15.7%
3 191
14.2%
4 88
 
6.6%
2 82
 
6.1%
1 78
 
5.8%
8 60
 
4.5%
7 53
 
4.0%
6 43
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1341
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 272
20.3%
- 223
16.6%
0 211
15.7%
3 191
14.2%
4 88
 
6.6%
2 82
 
6.1%
1 78
 
5.8%
8 60
 
4.5%
7 53
 
4.0%
6 43
 
3.2%

지번주소
Text

MISSING 

Distinct159
Distinct (%)90.9%
Missing5
Missing (%)2.8%
Memory size1.5 KiB
2023-12-13T00:24:05.507857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length23.022857
Min length16

Characters and Unicode

Total characters4029
Distinct characters93
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)82.9%

Sample

1st row경상남도 김해시 한림면 안하리 2001-9번지
2nd row경상남도 김해시 진례면 담안리 1432-11번지
3rd row경상남도 김해시 진례면 담안리 1462-9번지
4th row경상남도 김해시 구산동 707-11번지
5th row경상남도 김해시 한림면 퇴래리 313-1번지
ValueCountFrequency (%)
경상남도 175
20.5%
김해시 175
20.5%
한림면 48
 
5.6%
진영읍 29
 
3.4%
진례면 27
 
3.2%
주촌면 25
 
2.9%
내삼리 13
 
1.5%
본산리 10
 
1.2%
안하리 9
 
1.1%
부곡동 9
 
1.1%
Other values (211) 332
39.0%
2023-12-13T00:24:06.054794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
679
 
16.9%
상 181
 
4.5%
김 178
 
4.4%
해 178
 
4.4%
경 175
 
4.3%
남 175
 
4.3%
도 175
 
4.3%
시 175
 
4.3%
지 158
 
3.9%
번 152
 
3.8%
Other values (83) 1803
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2518
62.5%
Decimal Number 701
 
17.4%
Space Separator 679
 
16.9%
Dash Punctuation 129
 
3.2%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 181
 
7.2%
김 178
 
7.1%
해 178
 
7.1%
경 175
 
6.9%
남 175
 
6.9%
도 175
 
6.9%
시 175
 
6.9%
지 158
 
6.3%
번 152
 
6.0%
리 142
 
5.6%
Other values (69) 829
32.9%
Decimal Number
ValueCountFrequency (%)
1 152
21.7%
2 102
14.6%
3 67
9.6%
7 64
9.1%
4 59
 
8.4%
0 58
 
8.3%
6 53
 
7.6%
5 51
 
7.3%
9 49
 
7.0%
8 46
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
679
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2518
62.5%
Common 1509
37.5%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 181
 
7.2%
김 178
 
7.1%
해 178
 
7.1%
경 175
 
6.9%
남 175
 
6.9%
도 175
 
6.9%
시 175
 
6.9%
지 158
 
6.3%
번 152
 
6.0%
리 142
 
5.6%
Other values (69) 829
32.9%
Common
ValueCountFrequency (%)
679
45.0%
1 152
 
10.1%
- 129
 
8.5%
2 102
 
6.8%
3 67
 
4.4%
7 64
 
4.2%
4 59
 
3.9%
0 58
 
3.8%
6 53
 
3.5%
5 51
 
3.4%
Other values (2) 95
 
6.3%
Latin
ValueCountFrequency (%)
L 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2518
62.5%
ASCII 1511
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
679
44.9%
1 152
 
10.1%
- 129
 
8.5%
2 102
 
6.8%
3 67
 
4.4%
7 64
 
4.2%
4 59
 
3.9%
0 58
 
3.8%
6 53
 
3.5%
5 51
 
3.4%
Other values (4) 97
 
6.4%
Hangul
ValueCountFrequency (%)
상 181
 
7.2%
김 178
 
7.1%
해 178
 
7.1%
경 175
 
6.9%
남 175
 
6.9%
도 175
 
6.9%
시 175
 
6.9%
지 158
 
6.3%
번 152
 
6.0%
리 142
 
5.6%
Other values (69) 829
32.9%

도로명주소
Text

Distinct153
Distinct (%)85.5%
Missing1
Missing (%)0.6%
Memory size1.5 KiB
2023-12-13T00:24:06.447525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length24.128492
Min length19

Characters and Unicode

Total characters4319
Distinct characters94
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)74.3%

Sample

1st row경상남도 김해시 한림면 용덕로302번길 62
2nd row경상남도 김해시 진례면 고모로324번길 204
3rd row경상남도 김해시 진영읍 본산1로 80
4th row경상남도 김해시 한림면 김해대로927번길 145-4
5th row경상남도 김해시 진례면 고모로324번길 204
ValueCountFrequency (%)
경상남도 179
19.9%
김해시 179
19.9%
한림면 48
 
5.3%
진영읍 31
 
3.5%
진례면 27
 
3.0%
주촌면 25
 
2.8%
김해대로 11
 
1.2%
서부로1499번길 9
 
1.0%
상동면 8
 
0.9%
장유면 8
 
0.9%
Other values (235) 373
41.5%
2023-12-13T00:24:07.058287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
719
 
16.6%
김 205
 
4.7%
해 205
 
4.7%
상 194
 
4.5%
경 179
 
4.1%
남 179
 
4.1%
도 179
 
4.1%
시 179
 
4.1%
로 177
 
4.1%
1 164
 
3.8%
Other values (84) 1939
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2574
59.6%
Decimal Number 895
 
20.7%
Space Separator 719
 
16.6%
Dash Punctuation 79
 
1.8%
Open Punctuation 25
 
0.6%
Close Punctuation 25
 
0.6%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 205
 
8.0%
해 205
 
8.0%
상 194
 
7.5%
경 179
 
7.0%
남 179
 
7.0%
도 179
 
7.0%
시 179
 
7.0%
로 177
 
6.9%
면 123
 
4.8%
길 96
 
3.7%
Other values (69) 858
33.3%
Decimal Number
ValueCountFrequency (%)
1 164
18.3%
2 131
14.6%
4 97
10.8%
3 96
10.7%
9 93
10.4%
5 86
9.6%
7 63
 
7.0%
8 63
 
7.0%
0 56
 
6.3%
6 46
 
5.1%
Space Separator
ValueCountFrequency (%)
719
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2574
59.6%
Common 1745
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 205
 
8.0%
해 205
 
8.0%
상 194
 
7.5%
경 179
 
7.0%
남 179
 
7.0%
도 179
 
7.0%
시 179
 
7.0%
로 177
 
6.9%
면 123
 
4.8%
길 96
 
3.7%
Other values (69) 858
33.3%
Common
ValueCountFrequency (%)
719
41.2%
1 164
 
9.4%
2 131
 
7.5%
4 97
 
5.6%
3 96
 
5.5%
9 93
 
5.3%
5 86
 
4.9%
- 79
 
4.5%
7 63
 
3.6%
8 63
 
3.6%
Other values (5) 154
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2574
59.6%
ASCII 1745
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
719
41.2%
1 164
 
9.4%
2 131
 
7.5%
4 97
 
5.6%
3 96
 
5.5%
9 93
 
5.3%
5 86
 
4.9%
- 79
 
4.5%
7 63
 
3.6%
8 63
 
3.6%
Other values (5) 154
 
8.8%
Hangul
ValueCountFrequency (%)
김 205
 
8.0%
해 205
 
8.0%
상 194
 
7.5%
경 179
 
7.0%
남 179
 
7.0%
도 179
 
7.0%
시 179
 
7.0%
로 177
 
6.9%
면 123
 
4.8%
길 96
 
3.7%
Other values (69) 858
33.3%

위도
Real number (ℝ)

Distinct152
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.274973
Minimum35.187714
Maximum35.374028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:24:07.262748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.187714
5-th percentile35.217476
Q135.236306
median35.278742
Q335.306485
95-th percentile35.327076
Maximum35.374028
Range0.18631437
Interquartile range (IQR)0.07017915

Descriptive statistics

Standard deviation0.038833769
Coefficient of variation (CV)0.0011008873
Kurtosis-1.1654816
Mean35.274973
Median Absolute Deviation (MAD)0.034487075
Skewness-0.049172243
Sum6349.4951
Variance0.0015080616
MonotonicityNot monotonic
2023-12-13T00:24:07.441800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.21747636 4
 
2.2%
35.24636137 3
 
1.7%
35.25670211 3
 
1.7%
35.32688345 3
 
1.7%
35.3015698 3
 
1.7%
35.3145956 3
 
1.7%
35.28870418 2
 
1.1%
35.32503383 2
 
1.1%
35.25787416 2
 
1.1%
35.22002431 2
 
1.1%
Other values (142) 153
85.0%
ValueCountFrequency (%)
35.18771395 1
 
0.6%
35.20866529 1
 
0.6%
35.21396089 1
 
0.6%
35.21452656 1
 
0.6%
35.21704051 1
 
0.6%
35.21716095 1
 
0.6%
35.21747636 4
2.2%
35.21759874 1
 
0.6%
35.21786139 1
 
0.6%
35.21828529 1
 
0.6%
ValueCountFrequency (%)
35.37402832 1
0.6%
35.34388976 1
0.6%
35.33895646 1
0.6%
35.33791045 1
0.6%
35.33703301 1
0.6%
35.33310847 1
0.6%
35.33134424 1
0.6%
35.32743687 1
0.6%
35.32718232 1
0.6%
35.32707053 1
0.6%

경도
Real number (ℝ)

Distinct152
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.80551
Minimum128.71045
Maximum128.96381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:24:07.606975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.71045
5-th percentile128.73048
Q1128.76806
median128.79942
Q3128.83225
95-th percentile128.90681
Maximum128.96381
Range0.2533589
Interquartile range (IQR)0.064190525

Descriptive statistics

Standard deviation0.050521303
Coefficient of variation (CV)0.00039222936
Kurtosis-0.030461328
Mean128.80551
Median Absolute Deviation (MAD)0.0321533
Skewness0.64510149
Sum23184.992
Variance0.002552402
MonotonicityNot monotonic
2023-12-13T00:24:07.782985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.7988163 4
 
2.2%
128.7849764 3
 
1.7%
128.8696102 3
 
1.7%
128.7764498 3
 
1.7%
128.8327081 3
 
1.7%
128.7472865 3
 
1.7%
128.8039215 2
 
1.1%
128.7182474 2
 
1.1%
128.8169357 2
 
1.1%
128.8304932 2
 
1.1%
Other values (142) 153
85.0%
ValueCountFrequency (%)
128.7104526 1
0.6%
128.7166503 1
0.6%
128.7182474 2
1.1%
128.7186218 1
0.6%
128.7261927 1
0.6%
128.7271709 1
0.6%
128.7271933 1
0.6%
128.7280345 1
0.6%
128.7306113 1
0.6%
128.7428846 1
0.6%
ValueCountFrequency (%)
128.9638115 1
0.6%
128.9218342 1
0.6%
128.9172757 2
1.1%
128.9150805 1
0.6%
128.9121447 1
0.6%
128.9121206 1
0.6%
128.9114343 1
0.6%
128.9102788 1
0.6%
128.9066228 1
0.6%
128.9042504 1
0.6%

사용목적
Text

Distinct70
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T00:24:08.044681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length5.1944444
Min length2

Characters and Unicode

Total characters935
Distinct characters112
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

Unique48 ?
Unique (%)26.7%

Sample

1st row열처리용
2nd row특정고압가스 수소 사용폐지
3rd row열처리용
4th row열처리
5th row수소전지 충전용
ValueCountFrequency (%)
열처리용 45
18.2%
절단용 35
 
14.2%
절단 19
 
7.7%
의료용 15
 
6.1%
철판 11
 
4.5%
열처리 7
 
2.8%
및 6
 
2.4%
소재 6
 
2.4%
철판절단용 5
 
2.0%
용접 5
 
2.0%
Other values (70) 93
37.7%
2023-12-13T00:24:08.482594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 145
15.5%
절 92
 
9.8%
단 85
 
9.1%
67
 
7.2%
열 59
 
6.3%
리 59
 
6.3%
처 59
 
6.3%
철 27
 
2.9%
소 26
 
2.8%
판 24
 
2.6%
Other values (102) 292
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 818
87.5%
Space Separator 67
 
7.2%
Other Punctuation 12
 
1.3%
Uppercase Letter 12
 
1.3%
Lowercase Letter 10
 
1.1%
Decimal Number 6
 
0.6%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 145
17.7%
절 92
11.2%
단 85
 
10.4%
열 59
 
7.2%
리 59
 
7.2%
처 59
 
7.2%
철 27
 
3.3%
소 26
 
3.2%
판 24
 
2.9%
료 19
 
2.3%
Other values (75) 223
27.3%
Uppercase Letter
ValueCountFrequency (%)
C 4
33.3%
N 2
16.7%
B 1
 
8.3%
S 1
 
8.3%
P 1
 
8.3%
T 1
 
8.3%
F 1
 
8.3%
E 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
i 2
20.0%
e 2
20.0%
r 1
10.0%
g 1
10.0%
n 1
10.0%
a 1
10.0%
d 1
10.0%
l 1
10.0%
Decimal Number
ValueCountFrequency (%)
7 1
16.7%
8 1
16.7%
9 1
16.7%
1 1
16.7%
0 1
16.7%
2 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 10
83.3%
. 2
 
16.7%
Space Separator
ValueCountFrequency (%)
67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 818
87.5%
Common 95
 
10.2%
Latin 22
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 145
17.7%
절 92
11.2%
단 85
 
10.4%
열 59
 
7.2%
리 59
 
7.2%
처 59
 
7.2%
철 27
 
3.3%
소 26
 
3.2%
판 24
 
2.9%
료 19
 
2.3%
Other values (75) 223
27.3%
Latin
ValueCountFrequency (%)
C 4
18.2%
i 2
 
9.1%
N 2
 
9.1%
e 2
 
9.1%
B 1
 
4.5%
r 1
 
4.5%
g 1
 
4.5%
n 1
 
4.5%
a 1
 
4.5%
d 1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
67
70.5%
, 10
 
10.5%
) 5
 
5.3%
( 5
 
5.3%
. 2
 
2.1%
7 1
 
1.1%
8 1
 
1.1%
9 1
 
1.1%
1 1
 
1.1%
0 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 818
87.5%
ASCII 117
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 145
17.7%
절 92
11.2%
단 85
 
10.4%
열 59
 
7.2%
리 59
 
7.2%
처 59
 
7.2%
철 27
 
3.3%
소 26
 
3.2%
판 24
 
2.9%
료 19
 
2.3%
Other values (75) 223
27.3%
ASCII
ValueCountFrequency (%)
67
57.3%
, 10
 
8.5%
) 5
 
4.3%
( 5
 
4.3%
C 4
 
3.4%
i 2
 
1.7%
. 2
 
1.7%
N 2
 
1.7%
e 2
 
1.7%
B 1
 
0.9%
Other values (17) 17
 
14.5%

사용방법
Text

MISSING 

Distinct92
Distinct (%)57.1%
Missing19
Missing (%)10.6%
Memory size1.5 KiB
2023-12-13T00:24:08.745114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length30
Mean length8.4223602
Min length2

Characters and Unicode

Total characters1356
Distinct characters147
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

Unique78 ?
Unique (%)48.4%

Sample

1st row열처리용
2nd row폐지신고
3rd row열처리로에사용
4th row열처리용
5th row수소전지 충전용
ValueCountFrequency (%)
열처리용 31
 
9.2%
절단용 16
 
4.7%
공급 15
 
4.5%
사용 15
 
4.5%
기화후 14
 
4.2%
액화산소 13
 
3.9%
절단 11
 
3.3%
의료용 10
 
3.0%
배관을 9
 
2.7%
배관으로 8
 
2.4%
Other values (117) 195
57.9%
2023-12-13T00:24:09.119480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
13.0%
용 122
 
9.0%
기 65
 
4.8%
화 60
 
4.4%
절 53
 
3.9%
소 52
 
3.8%
단 50
 
3.7%
처 45
 
3.3%
리 44
 
3.2%
열 43
 
3.2%
Other values (137) 646
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1126
83.0%
Space Separator 176
 
13.0%
Lowercase Letter 17
 
1.3%
Uppercase Letter 13
 
1.0%
Other Punctuation 8
 
0.6%
Decimal Number 8
 
0.6%
Open Punctuation 4
 
0.3%
Close Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 122
 
10.8%
기 65
 
5.8%
화 60
 
5.3%
절 53
 
4.7%
소 52
 
4.6%
단 50
 
4.4%
처 45
 
4.0%
리 44
 
3.9%
열 43
 
3.8%
산 42
 
3.7%
Other values (107) 550
48.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
17.6%
l 2
11.8%
n 2
11.8%
i 2
11.8%
g 2
11.8%
k 1
 
5.9%
r 1
 
5.9%
a 1
 
5.9%
f 1
 
5.9%
o 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
15.4%
P 2
15.4%
T 2
15.4%
G 1
7.7%
L 1
7.7%
N 1
7.7%
B 1
7.7%
F 1
7.7%
E 1
7.7%
S 1
7.7%
Other Punctuation
ValueCountFrequency (%)
, 5
62.5%
. 2
 
25.0%
: 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
9 4
50.0%
4 3
37.5%
7 1
 
12.5%
Space Separator
ValueCountFrequency (%)
176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1126
83.0%
Common 200
 
14.7%
Latin 30
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 122
 
10.8%
기 65
 
5.8%
화 60
 
5.3%
절 53
 
4.7%
소 52
 
4.6%
단 50
 
4.4%
처 45
 
4.0%
리 44
 
3.9%
열 43
 
3.8%
산 42
 
3.7%
Other values (107) 550
48.8%
Latin
ValueCountFrequency (%)
e 3
 
10.0%
C 2
 
6.7%
P 2
 
6.7%
T 2
 
6.7%
l 2
 
6.7%
n 2
 
6.7%
i 2
 
6.7%
g 2
 
6.7%
G 1
 
3.3%
k 1
 
3.3%
Other values (11) 11
36.7%
Common
ValueCountFrequency (%)
176
88.0%
, 5
 
2.5%
( 4
 
2.0%
) 4
 
2.0%
9 4
 
2.0%
4 3
 
1.5%
. 2
 
1.0%
7 1
 
0.5%
: 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1126
83.0%
ASCII 230
 
17.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
76.5%
, 5
 
2.2%
( 4
 
1.7%
) 4
 
1.7%
9 4
 
1.7%
4 3
 
1.3%
e 3
 
1.3%
. 2
 
0.9%
C 2
 
0.9%
P 2
 
0.9%
Other values (20) 25
 
10.9%
Hangul
ValueCountFrequency (%)
용 122
 
10.8%
기 65
 
5.8%
화 60
 
5.3%
절 53
 
4.7%
소 52
 
4.6%
단 50
 
4.4%
처 45
 
4.0%
리 44
 
3.9%
열 43
 
3.8%
산 42
 
3.7%
Other values (107) 550
48.8%

월사용량
Real number (ℝ)

ZEROS 

Distinct58
Distinct (%)32.4%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean3195.7261
Minimum0
Maximum20000
Zeros14
Zeros (%)7.8%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:24:09.277943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1500
median1680
Q33900
95-th percentile10500
Maximum20000
Range20000
Interquartile range (IQR)3400

Descriptive statistics

Standard deviation4249.4317
Coefficient of variation (CV)1.3297234
Kurtosis4.3594368
Mean3195.7261
Median Absolute Deviation (MAD)1320
Skewness2.1037954
Sum572034.98
Variance18057670
MonotonicityNot monotonic
2023-12-13T00:24:09.439970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000.0 16
 
8.9%
0.0 14
 
7.8%
10000.0 12
 
6.7%
3000.0 12
 
6.7%
1000.0 9
 
5.0%
400.0 7
 
3.9%
500.0 7
 
3.9%
1500.0 5
 
2.8%
100.0 5
 
2.8%
15000.0 5
 
2.8%
Other values (48) 87
48.3%
ValueCountFrequency (%)
0.0 14
7.8%
4.977 1
 
0.6%
10.0 1
 
0.6%
50.0 1
 
0.6%
80.0 1
 
0.6%
100.0 5
 
2.8%
130.0 1
 
0.6%
150.0 1
 
0.6%
173.0 1
 
0.6%
180.0 2
 
1.1%
ValueCountFrequency (%)
20000.0 2
 
1.1%
19800.0 1
 
0.6%
18000.0 1
 
0.6%
15000.0 5
2.8%
10000.0 12
6.7%
9000.0 1
 
0.6%
8500.0 1
 
0.6%
8000.0 3
 
1.7%
7056.0 1
 
0.6%
7000.0 2
 
1.1%

수용정원수
Real number (ℝ)

ZEROS 

Distinct48
Distinct (%)26.8%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean33.77095
Minimum0
Maximum300
Zeros19
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:24:09.577698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.5
median10
Q329
95-th percentile202.6
Maximum300
Range300
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation64.346482
Coefficient of variation (CV)1.9053797
Kurtosis8.0426432
Mean33.77095
Median Absolute Deviation (MAD)8
Skewness2.9399991
Sum6045
Variance4140.4697
MonotonicityNot monotonic
2023-12-13T00:24:09.733227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
10 23
 
12.8%
0 19
 
10.6%
5 11
 
6.1%
30 10
 
5.6%
3 10
 
5.6%
6 9
 
5.0%
2 9
 
5.0%
12 9
 
5.0%
15 8
 
4.4%
25 6
 
3.3%
Other values (38) 65
36.1%
ValueCountFrequency (%)
0 19
10.6%
1 2
 
1.1%
2 9
5.0%
3 10
5.6%
4 5
 
2.8%
5 11
6.1%
6 9
5.0%
7 3
 
1.7%
8 5
 
2.8%
9 2
 
1.1%
ValueCountFrequency (%)
300 1
0.6%
292 2
1.1%
291 1
0.6%
278 1
0.6%
270 1
0.6%
250 2
1.1%
208 1
0.6%
202 1
0.6%
200 1
0.6%
170 1
0.6%

Interactions

2023-12-13T00:24:02.288504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:00.808473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.281330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.771111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:02.453899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:00.935053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.403696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.905660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:02.590630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.038949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.536700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:02.026243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:02.715057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.159632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:01.667485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:24:02.163071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:24:09.833459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명전화번호위도경도사용목적사용방법월사용량수용정원수
영업상태명1.0000.9810.3770.0000.6800.3930.0000.422
전화번호0.9811.0000.9970.9980.9700.9570.9710.000
위도0.3770.9971.0000.7310.7530.8200.0000.358
경도0.0000.9980.7311.0000.6490.6740.0000.420
사용목적0.6800.9700.7530.6491.0000.9980.8560.728
사용방법0.3930.9570.8200.6740.9981.0000.9160.800
월사용량0.0000.9710.0000.0000.8560.9161.0000.000
수용정원수0.4220.0000.3580.4200.7280.8000.0001.000
2023-12-13T00:24:09.941792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도월사용량수용정원수영업상태명
위도1.000-0.3580.2610.0970.239
경도-0.3581.000-0.1400.0310.000
월사용량0.261-0.1401.0000.2940.000
수용정원수0.0970.0310.2941.0000.227
영업상태명0.2390.0000.0000.2271.000

Missing values

2023-12-13T00:24:02.903542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:24:03.421239image/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.
2023-12-13T00:24:03.546273image/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

사업장명영업상태명전화번호지번주소도로명주소위도경도사용목적사용방법월사용량수용정원수
0(주)풍성정밀관폐업<NA>경상남도 김해시 한림면 안하리 2001-9번지경상남도 김해시 한림면 용덕로302번길 6235.30012128.832097열처리용열처리용2000.030
1하이에어코리아(주)폐업<NA>경상남도 김해시 진례면 담안리 1432-11번지경상남도 김해시 진례면 고모로324번길 20435.246361128.784976특정고압가스 수소 사용폐지폐지신고0.0250
2홍경에이치엔티폐업<NA><NA>경상남도 김해시 진영읍 본산1로 8035.314596128.747287열처리용열처리로에사용100.06
3대동브레이징폐업<NA><NA>경상남도 김해시 한림면 김해대로927번길 145-435.302874128.788343열처리열처리용400.07
4하이에어코리아(주)폐업<NA>경상남도 김해시 진례면 담안리 1462-9번지경상남도 김해시 진례면 고모로324번길 20435.246361128.784976수소전지 충전용수소전지 충전용700.0250
5강일병원폐업<NA>경상남도 김해시 구산동 707-11번지경상남도 김해시 가락로 359 (구산동)35.256702128.86961의료용(취소원 제출 2017.9.8)의료용750.0208
6(주)영한스틸폐업<NA><NA>경상남도 김해시 상동면 상동로 17835.301383128.891637선박구성부분품 절딘(CNC절단기)선박구성부분품 절딘(CNC절단기)4.9773
7홍경에이치엔티폐업<NA><NA>경상남도 김해시 진영읍 본산1로 8035.314596128.747287열처리용열처리150.018
8DH산업폐업<NA>경상남도 김해시 한림면 퇴래리 313-1번지경상남도 김해시 한림면 김해대로927번길 23935.306485128.792487절단 및 절곡용배관으로 공급10000.08
9(주)광진사폐업<NA>경상남도 김해시 진례면 송현리 387-4번지경상남도 김해시 진례면 담안로 16635.253939128.765492브레이징(용접용)저장실에 용기를 저장하여 배관을 통하여 공급200.010
사업장명영업상태명전화번호지번주소도로명주소위도경도사용목적사용방법월사용량수용정원수
170호승열처리영업055-337-3678경상남도 김해시 주촌면 내삼리 1134-13번지경상남도 김해시 주촌면 서부로1499번길 6835.232337128.812964열처리용열처리용2000.010
171(주)유넥스영업055-310-9100경상남도 김해시 주촌면 망덕리 873-4경상남도 김해시 주촌면 골든루트로130번길 5735.220024128.830493절단잘단가스4000.0100
172(주)대우에스티아이폐업<NA>경상남도 김해시 한림면 안하리 1B 5L<NA>35.319554128.823389철판 절단 및 절곡<NA>3000.00
173월드테크휴업055-337-3679경상남도 김해시 주촌면 내삼리 1134경상남도 김해시 주촌면 서부로1499번길 68 내삼리113435.232337128.812964열처리용열처리용224.06
174대흥공업(주)휴업055-310-6700경상남도 김해시 한림면 병동리 644-1경상남도 김해시 한림면 김해대로974번길 13535.28208128.791063철판,단조물 절단용절단용15000.05
175(주)광성휴업055-338-9973경상남도 김해시 생림면 생철리 212-2번지경상남도 김해시 생림면 생림대로928번길 8135.34389128.85447산소용접 및 절단산소용접 및 절단2000.030
176(주)효산 진영지점휴업055-343-7600경상남도 김해시 진영읍 진영리 674-16경상남도 김해시 진영읍 진산대로 244-1135.325034128.718247열처리용<NA>2500.025
177(주)재원철강휴업055-342-4321경상남도 김해시 진영읍 의전리 177-2번지경상남도 김해시 진영읍 서부로378번길 2135.269791128.753194절단용용기4500.09
178(주)한영기계영업055-346-4800경상남도 김해시 진례면 송현리 1289-225번지경상남도 김해시 진례면 고모로134번길 54-4835.236575128.774254열처리용열처리용300.03
179삼영기업영업055-342-2901경상남도 김해시 진영읍 본산리 307-2 번지경상남도 김해시 진영읍 본산로 26235.31554128.754141절단용(철판)<NA><NA><NA>

Duplicate rows

Most frequently occurring

사업장명영업상태명전화번호지번주소도로명주소위도경도사용목적사용방법월사용량수용정원수# duplicates
0(주)엔디케이휴업055-326-4243경상남도 김해시 안동 541-23번지경상남도 김해시 김해대로2596번길 93 (안동)35.22567128.917276열처리용열처리용1000.032