Overview

Dataset statistics

Number of variables8
Number of observations49
Missing cells13
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory66.7 B

Variable types

Categorical4
Text4

Dataset

Descriptionㅇ 2023.3.20.기준 대전광역시 관내 측량업 등록 현황 자료로서 지적측량 등 측량 의뢰시 선택하여 접수 가능합니다 - 공공측량업, 지적측량업, 일반측량업
URLhttps://www.data.go.kr/data/15062315/fileData.do

Alerts

시도시군구 has constant value ""Constant
본점지점 has constant value ""Constant
사무소전화번호 has 2 (4.1%) missing valuesMissing
사무소팩스번호 has 11 (22.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:52:22.950476
Analysis finished2023-12-12 08:52:24.133819
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
대전광역시
49 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 49
100.0%

Length

2023-12-12T17:52:24.207480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:24.298510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 49
100.0%

업종
Categorical

Distinct3
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
일반측량
33 
공공측량
10 
지적측량
6 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반측량
2nd row일반측량
3rd row지적측량
4th row일반측량
5th row일반측량

Common Values

ValueCountFrequency (%)
일반측량 33
67.3%
공공측량 10
 
20.4%
지적측량 6
 
12.2%

Length

2023-12-12T17:52:24.392751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:24.484919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반측량 33
67.3%
공공측량 10
 
20.4%
지적측량 6
 
12.2%

업체명
Text

Distinct45
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T17:52:24.668200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length9.122449
Min length4

Characters and Unicode

Total characters447
Distinct characters103
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

Unique41 ?
Unique (%)83.7%

Sample

1st row미래토목설계
2nd row주식회사 동선이앤씨
3rd row티알정보기술 주식회사
4th row두영안전(주)
5th row(주)예닮엔지니어링
ValueCountFrequency (%)
주식회사 8
 
13.1%
주)중부기술단 2
 
3.3%
신의이엔지 2
 
3.3%
티알정보기술 2
 
3.3%
이엔지정보기술(주 2
 
3.3%
주)한울이엔씨 1
 
1.6%
주 1
 
1.6%
신화엔지니어링 1
 
1.6%
종합 1
 
1.6%
건축사 1
 
1.6%
Other values (40) 40
65.6%
2023-12-12T17:52:25.050479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 34
 
7.6%
( 27
 
6.0%
) 27
 
6.0%
엔 22
 
4.9%
지 22
 
4.9%
사 17
 
3.8%
이 13
 
2.9%
링 12
 
2.7%
기 12
 
2.7%
어 12
 
2.7%
Other values (93) 249
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 378
84.6%
Open Punctuation 27
 
6.0%
Close Punctuation 27
 
6.0%
Space Separator 12
 
2.7%
Uppercase Letter 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 34
 
9.0%
엔 22
 
5.8%
지 22
 
5.8%
사 17
 
4.5%
이 13
 
3.4%
링 12
 
3.2%
기 12
 
3.2%
어 12
 
3.2%
니 12
 
3.2%
술 11
 
2.9%
Other values (87) 211
55.8%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
G 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 378
84.6%
Common 66
 
14.8%
Latin 3
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 34
 
9.0%
엔 22
 
5.8%
지 22
 
5.8%
사 17
 
4.5%
이 13
 
3.4%
링 12
 
3.2%
기 12
 
3.2%
어 12
 
3.2%
니 12
 
3.2%
술 11
 
2.9%
Other values (87) 211
55.8%
Common
ValueCountFrequency (%)
( 27
40.9%
) 27
40.9%
12
18.2%
Latin
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 378
84.6%
ASCII 69
 
15.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 34
 
9.0%
엔 22
 
5.8%
지 22
 
5.8%
사 17
 
4.5%
이 13
 
3.4%
링 12
 
3.2%
기 12
 
3.2%
어 12
 
3.2%
니 12
 
3.2%
술 11
 
2.9%
Other values (87) 211
55.8%
ASCII
ValueCountFrequency (%)
( 27
39.1%
) 27
39.1%
12
17.4%
E 1
 
1.4%
N 1
 
1.4%
G 1
 
1.4%

개인법인
Categorical

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
법인
35 
개인
14 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row법인
3rd row법인
4th row법인
5th row법인

Common Values

ValueCountFrequency (%)
법인 35
71.4%
개인 14
 
28.6%

Length

2023-12-12T17:52:25.178629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:25.288860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 35
71.4%
개인 14
 
28.6%

본점지점
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
본점
49 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본점 49
100.0%

Length

2023-12-12T17:52:25.383137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:25.465185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 49
100.0%

사무소전화번호
Text

MISSING 

Distinct41
Distinct (%)87.2%
Missing2
Missing (%)4.1%
Memory size524.0 B
2023-12-12T17:52:25.656012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.085106
Min length12

Characters and Unicode

Total characters568
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

Unique35 ?
Unique (%)74.5%

Sample

1st row042-543-9092
2nd row042-621-7115
3rd row042-322-2288
4th row070-4161-3100
5th row042-933-1140
ValueCountFrequency (%)
042-673-1058 2
 
4.3%
042-528-2301 2
 
4.3%
042-623-7868 2
 
4.3%
042-322-2288 2
 
4.3%
042-862-0011 2
 
4.3%
042-345-2246 2
 
4.3%
042-628-8222 1
 
2.1%
042-622-2450 1
 
2.1%
042-536-3705 1
 
2.1%
042-489-3173 1
 
2.1%
Other values (31) 31
66.0%
2023-12-12T17:52:26.091716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 99
17.4%
- 94
16.5%
0 77
13.6%
4 70
12.3%
8 45
7.9%
6 40
7.0%
3 37
 
6.5%
1 32
 
5.6%
7 29
 
5.1%
5 29
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 474
83.5%
Dash Punctuation 94
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 99
20.9%
0 77
16.2%
4 70
14.8%
8 45
9.5%
6 40
8.4%
3 37
 
7.8%
1 32
 
6.8%
7 29
 
6.1%
5 29
 
6.1%
9 16
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 568
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 99
17.4%
- 94
16.5%
0 77
13.6%
4 70
12.3%
8 45
7.9%
6 40
7.0%
3 37
 
6.5%
1 32
 
5.6%
7 29
 
5.1%
5 29
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 99
17.4%
- 94
16.5%
0 77
13.6%
4 70
12.3%
8 45
7.9%
6 40
7.0%
3 37
 
6.5%
1 32
 
5.6%
7 29
 
5.1%
5 29
 
5.1%

사무소팩스번호
Text

MISSING 

Distinct33
Distinct (%)86.8%
Missing11
Missing (%)22.4%
Memory size524.0 B
2023-12-12T17:52:26.305103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters456
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

Unique28 ?
Unique (%)73.7%

Sample

1st row042-621-7116
2nd row042-322-2299
3rd row042-822-1205
4th row042-933-1141
5th row042-716-0934
ValueCountFrequency (%)
042-623-7869 2
 
5.3%
042-345-2248 2
 
5.3%
042-322-2299 2
 
5.3%
042-862-1441 2
 
5.3%
042-637-5638 2
 
5.3%
042-480-9515 1
 
2.6%
042-223-3664 1
 
2.6%
042-826-6402 1
 
2.6%
042-484-3923 1
 
2.6%
042-825-7286 1
 
2.6%
Other values (23) 23
60.5%
2023-12-12T17:52:26.679639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 82
18.0%
- 76
16.7%
4 67
14.7%
0 48
10.5%
6 34
7.5%
3 33
7.2%
8 31
 
6.8%
1 25
 
5.5%
5 23
 
5.0%
7 21
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
83.3%
Dash Punctuation 76
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 82
21.6%
4 67
17.6%
0 48
12.6%
6 34
8.9%
3 33
8.7%
8 31
 
8.2%
1 25
 
6.6%
5 23
 
6.1%
7 21
 
5.5%
9 16
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 82
18.0%
- 76
16.7%
4 67
14.7%
0 48
10.5%
6 34
7.5%
3 33
7.2%
8 31
 
6.8%
1 25
 
5.5%
5 23
 
5.0%
7 21
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 82
18.0%
- 76
16.7%
4 67
14.7%
0 48
10.5%
6 34
7.5%
3 33
7.2%
8 31
 
6.8%
1 25
 
5.5%
5 23
 
5.0%
7 21
 
4.6%

사무소도로명주소
Text

Distinct44
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T17:52:27.017126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length51
Mean length41.428571
Min length30

Characters and Unicode

Total characters2030
Distinct characters146
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)79.6%

Sample

1st row대전광역시 서구 관저중로95번길 57 201호(관저동) 우)35372
2nd row대전광역시 유성구 북유성대로 303 1002호(반석동) 우)34068
3rd row대전광역시 유성구 계룡로18번길 16 2층 (구암동) 우)34176
4th row대전광역시 유성구 온천로 53 (봉명동) 우)34186
5th row대전광역시 유성구 대학로81번길 38 401호(궁동) 우)34167
ValueCountFrequency (%)
대전광역시 49
 
14.2%
유성구 26
 
7.5%
서구 12
 
3.5%
봉명동 6
 
1.7%
우)34186 5
 
1.4%
대학로 5
 
1.4%
중구 4
 
1.2%
동구 4
 
1.2%
노블레스타워 4
 
1.2%
어은동 4
 
1.2%
Other values (178) 227
65.6%
2023-12-12T17:52:27.481399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
349
 
17.2%
) 100
 
4.9%
3 88
 
4.3%
1 80
 
3.9%
4 74
 
3.6%
대 73
 
3.6%
동 65
 
3.2%
2 64
 
3.2%
구 55
 
2.7%
5 54
 
2.7%
Other values (136) 1028
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 945
46.6%
Decimal Number 522
25.7%
Space Separator 349
 
17.2%
Close Punctuation 100
 
4.9%
Open Punctuation 51
 
2.5%
Other Punctuation 45
 
2.2%
Dash Punctuation 14
 
0.7%
Letter Number 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 73
 
7.7%
동 65
 
6.9%
구 55
 
5.8%
전 52
 
5.5%
시 51
 
5.4%
광 49
 
5.2%
역 49
 
5.2%
우 49
 
5.2%
로 48
 
5.1%
유 30
 
3.2%
Other values (117) 424
44.9%
Decimal Number
ValueCountFrequency (%)
3 88
16.9%
1 80
15.3%
4 74
14.2%
2 64
12.3%
5 54
10.3%
0 48
9.2%
8 33
 
6.3%
9 29
 
5.6%
6 28
 
5.4%
7 24
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 44
97.8%
· 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
F 1
50.0%
Space Separator
ValueCountFrequency (%)
349
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1081
53.3%
Hangul 945
46.6%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 73
 
7.7%
동 65
 
6.9%
구 55
 
5.8%
전 52
 
5.5%
시 51
 
5.4%
광 49
 
5.2%
역 49
 
5.2%
우 49
 
5.2%
로 48
 
5.1%
유 30
 
3.2%
Other values (117) 424
44.9%
Common
ValueCountFrequency (%)
349
32.3%
) 100
 
9.3%
3 88
 
8.1%
1 80
 
7.4%
4 74
 
6.8%
2 64
 
5.9%
5 54
 
5.0%
( 51
 
4.7%
0 48
 
4.4%
, 44
 
4.1%
Other values (6) 129
 
11.9%
Latin
ValueCountFrequency (%)
Ⅱ 2
50.0%
B 1
25.0%
F 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1082
53.3%
Hangul 945
46.6%
Number Forms 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
349
32.3%
) 100
 
9.2%
3 88
 
8.1%
1 80
 
7.4%
4 74
 
6.8%
2 64
 
5.9%
5 54
 
5.0%
( 51
 
4.7%
0 48
 
4.4%
, 44
 
4.1%
Other values (7) 130
 
12.0%
Hangul
ValueCountFrequency (%)
대 73
 
7.7%
동 65
 
6.9%
구 55
 
5.8%
전 52
 
5.5%
시 51
 
5.4%
광 49
 
5.2%
역 49
 
5.2%
우 49
 
5.2%
로 48
 
5.1%
유 30
 
3.2%
Other values (117) 424
44.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

Correlations

2023-12-12T17:52:27.606147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업체명개인법인사무소전화번호사무소팩스번호사무소도로명주소
업종1.0000.0000.1770.0000.0000.000
업체명0.0001.0001.0001.0001.0001.000
개인법인0.1771.0001.0000.8911.0001.000
사무소전화번호0.0001.0000.8911.0001.0000.998
사무소팩스번호0.0001.0001.0001.0001.0001.000
사무소도로명주소0.0001.0001.0000.9981.0001.000
2023-12-12T17:52:27.716103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개인법인업종
개인법인1.0000.287
업종0.2871.000
2023-12-12T17:52:27.801615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종개인법인
업종1.0000.287
개인법인0.2871.000

Missing values

2023-12-12T17:52:23.803489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:52:23.972355image/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.
2023-12-12T17:52:24.082856image/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

시도시군구업종업체명개인법인본점지점사무소전화번호사무소팩스번호사무소도로명주소
0대전광역시일반측량미래토목설계개인본점042-543-9092<NA>대전광역시 서구 관저중로95번길 57 201호(관저동) 우)35372
1대전광역시일반측량주식회사 동선이앤씨법인본점042-621-7115042-621-7116대전광역시 유성구 북유성대로 303 1002호(반석동) 우)34068
2대전광역시지적측량티알정보기술 주식회사법인본점042-322-2288042-322-2299대전광역시 유성구 계룡로18번길 16 2층 (구암동) 우)34176
3대전광역시일반측량두영안전(주)법인본점<NA><NA>대전광역시 유성구 온천로 53 (봉명동) 우)34186
4대전광역시일반측량(주)예닮엔지니어링법인본점070-4161-3100042-822-1205대전광역시 유성구 대학로81번길 38 401호(궁동) 우)34167
5대전광역시일반측량대영드론솔루션(주)법인본점042-933-1140042-933-1141대전광역시 유성구 테크노9로 35(탑립동), 3층4호 우)34027
6대전광역시일반측량한국산지보전협회개인본점042-716-0930042-716-0934대전광역시 서구 문정로40번길 51(탄방동), 창민빌딩 5층 우)35262
7대전광역시공공측량(주)무브먼츠법인본점070-7769-0529<NA>대전광역시 유성구 유성대로1689번길 125, 한국수자원공사연구원 연구2동 1층 스타트업 허브5호실(전민동) 우)34045
8대전광역시공공측량주식회사 선화에스앤지법인본점042-822-8636042-822-8637대전광역시 중구 계백로 1719 , 8층 18호 (오류동) 우)34909
9대전광역시공공측량주식회사 신의이엔지법인본점042-862-0011042-862-1441대전광역시 유성구 수통골로 91 (덕명동), 우)34154
시도시군구업종업체명개인법인본점지점사무소전화번호사무소팩스번호사무소도로명주소
39대전광역시일반측량중앙토목측량설계사무소개인본점042-484-3924042-484-3923대전광역시 유성구 대학로 195-1 (어은동), 3층 우)34139
40대전광역시일반측량(주)상우기술단법인본점042-826-7280042-825-7286대전광역시 유성구 노은서로76번길 77 (노은동), 상연빌딩 301호, 302호 우)34092
41대전광역시일반측량(주)경림엔지니어링법인본점042-488-6642042-480-9515대전광역시 서구 월평로 48 (월평동), 우)35225
42대전광역시지적측량(주)중부기술단법인본점042-673-1058042-637-5638대전광역시 동구 동서대로 1647 (용전동) 우)34552
43대전광역시일반측량(주)세영엔지니어링법인본점042-476-5669042-483-5719대전광역시 유성구 온천북로 73, 204호 (봉명동, 투유1) 우)34185
44대전광역시일반측량(합)대창엔지니어링법인본점042-489-3173042-489-3176대전광역시 서구 둔산대로117번길 44-0 912호 (만년동, 엑스포오피스텔) 우)35203
45대전광역시일반측량우정토목측량설계공사개인본점042-536-3705042-5363-704대전광역시 서구 도솔로 327 (괴정동), 미소빌라 201호 우)35292
46대전광역시일반측량(주)현대토목법인본점042-825-9738042-826-3924대전광역시 유성구 어은로 44 (어은동), 4층 우)34139
47대전광역시공공측량(주)선구엔지니어링법인본점042-476-6330042-476-7330대전광역시 유성구 은구비남로7번길 19 (지족동), 201호(지족동,거성빌딩) 우)34087
48대전광역시지적측량이엔지정보기술(주)법인본점042-345-2246042-345-2248대전광역시 대덕구 계족로 593-0 (중리동) 우)34389