Overview

Dataset statistics

Number of variables23
Number of observations1053
Missing cells5696
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory193.5 KiB
Average record size in memory188.1 B

Variable types

Text8
Categorical9
Numeric4
DateTime2

Dataset

Description구직신청번호,성별,나이,학력공통코드,학력공통코드명,희망근무지역(시도)_1,희망근무지역명(시군구)_1,희망근무지역명(시도)_2,희망근무지역명(시군구)_2,희망직종공통코드,희망직종공통코드명,희망직종경력년수,희망직종경력개월수,희망직종경력년_월수,구직인증상태공통구분,구직인증상태공통구분명,검색키워드1,검색키워드2,검색키워드3,검색키워드4,검색키워드5,등록일시,수정일시
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21055/S/1/datasetView.do

Alerts

희망근무지역(시도)_1 is highly imbalanced (90.3%)Imbalance
희망근무지역명(시도)_2 is highly imbalanced (59.2%)Imbalance
희망직종경력년수 has 433 (41.1%) missing valuesMissing
희망직종경력개월수 has 433 (41.1%) missing valuesMissing
검색키워드1 has 908 (86.2%) missing valuesMissing
검색키워드2 has 938 (89.1%) missing valuesMissing
검색키워드3 has 972 (92.3%) missing valuesMissing
검색키워드4 has 996 (94.6%) missing valuesMissing
검색키워드5 has 1015 (96.4%) missing valuesMissing
구직신청번호 has unique valuesUnique
희망직종경력년수 has 102 (9.7%) zerosZeros
희망직종경력개월수 has 461 (43.8%) zerosZeros

Reproduction

Analysis started2024-05-04 03:26:14.907311
Analysis finished2024-05-04 03:26:16.510532
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구직신청번호
Text

UNIQUE 

Distinct1053
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
2024-05-04T03:26:16.724497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters16848
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1053 ?
Unique (%)100.0%

Sample

1st rowH301202405032563
2nd rowH321202405032562
3rd rowH323202405032561
4th rowH311202405032547
5th rowH322202405032546
ValueCountFrequency (%)
h301202405032563 1
 
0.1%
h318202405020839 1
 
0.1%
h311202405021027 1
 
0.1%
h309202405021026 1
 
0.1%
h323202405021008 1
 
0.1%
h320202405020997 1
 
0.1%
h309202405020995 1
 
0.1%
h309202405020981 1
 
0.1%
h311202405020964 1
 
0.1%
h311202405020949 1
 
0.1%
Other values (1043) 1043
99.1%
2024-05-04T03:26:17.510353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4442
26.4%
2 3502
20.8%
3 1731
 
10.3%
4 1581
 
9.4%
1 1575
 
9.3%
5 1394
 
8.3%
H 1053
 
6.2%
9 426
 
2.5%
8 399
 
2.4%
6 393
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15795
93.8%
Uppercase Letter 1053
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4442
28.1%
2 3502
22.2%
3 1731
 
11.0%
4 1581
 
10.0%
1 1575
 
10.0%
5 1394
 
8.8%
9 426
 
2.7%
8 399
 
2.5%
6 393
 
2.5%
7 352
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
H 1053
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15795
93.8%
Latin 1053
 
6.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4442
28.1%
2 3502
22.2%
3 1731
 
11.0%
4 1581
 
10.0%
1 1575
 
10.0%
5 1394
 
8.8%
9 426
 
2.7%
8 399
 
2.5%
6 393
 
2.5%
7 352
 
2.2%
Latin
ValueCountFrequency (%)
H 1053
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16848
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4442
26.4%
2 3502
20.8%
3 1731
 
10.3%
4 1581
 
9.4%
1 1575
 
9.3%
5 1394
 
8.3%
H 1053
 
6.2%
9 426
 
2.5%
8 399
 
2.4%
6 393
 
2.3%

성별
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
여
567 
남
486 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여 567
53.8%
남 486
46.2%

Length

2024-05-04T03:26:17.905138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:26:18.195724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 567
53.8%
남 486
46.2%

나이
Real number (ℝ)

Distinct65
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.545109
Minimum18
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2024-05-04T03:26:18.479855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile27.6
Q157
median63
Q369
95-th percentile76
Maximum84
Range66
Interquartile range (IQR)12

Descriptive statistics

Standard deviation12.804063
Coefficient of variation (CV)0.21147972
Kurtosis1.8750811
Mean60.545109
Median Absolute Deviation (MAD)6
Skewness-1.4498118
Sum63754
Variance163.94402
MonotonicityNot monotonic
2024-05-04T03:26:18.736009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63 62
 
5.9%
69 60
 
5.7%
64 54
 
5.1%
61 52
 
4.9%
68 51
 
4.8%
67 49
 
4.7%
65 48
 
4.6%
66 47
 
4.5%
71 43
 
4.1%
60 43
 
4.1%
Other values (55) 544
51.7%
ValueCountFrequency (%)
18 1
 
0.1%
20 4
0.4%
21 2
 
0.2%
22 5
0.5%
23 6
0.6%
24 9
0.9%
25 9
0.9%
26 8
0.8%
27 9
0.9%
28 5
0.5%
ValueCountFrequency (%)
84 1
 
0.1%
83 1
 
0.1%
82 2
 
0.2%
81 3
 
0.3%
80 5
 
0.5%
79 4
 
0.4%
78 12
1.1%
77 12
1.1%
76 14
1.3%
75 11
1.0%

학력공통코드
Categorical

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
J00106
387 
J00110
225 
J00104
193 
J00102
89 
J00108
83 
Other values (4)
76 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJ00100
2nd rowJ00106
3rd rowJ00110
4th rowJ00108
5th rowJ00108

Common Values

ValueCountFrequency (%)
J00106 387
36.8%
J00110 225
21.4%
J00104 193
18.3%
J00102 89
 
8.5%
J00108 83
 
7.9%
J00100 44
 
4.2%
J00112 16
 
1.5%
J00101 13
 
1.2%
J00114 3
 
0.3%

Length

2024-05-04T03:26:19.067035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:26:19.398378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
j00106 387
36.8%
j00110 225
21.4%
j00104 193
18.3%
j00102 89
 
8.5%
j00108 83
 
7.9%
j00100 44
 
4.2%
j00112 16
 
1.5%
j00101 13
 
1.2%
j00114 3
 
0.3%

학력공통코드명
Categorical

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
고등학교
387 
대학_대학교
225 
중학교
193 
초등학교
89 
전문대학
83 
Other values (4)
76 

Length

Max length6
Median length4
Mean length4.2317189
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관계없음
2nd row고등학교
3rd row대학_대학교
4th row전문대학
5th row전문대학

Common Values

ValueCountFrequency (%)
고등학교 387
36.8%
대학_대학교 225
21.4%
중학교 193
18.3%
초등학교 89
 
8.5%
전문대학 83
 
7.9%
관계없음 44
 
4.2%
석사과정 16
 
1.5%
무학력 13
 
1.2%
박사과정 3
 
0.3%

Length

2024-05-04T03:26:19.821785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:26:20.154884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고등학교 387
36.8%
대학_대학교 225
21.4%
중학교 193
18.3%
초등학교 89
 
8.5%
전문대학 83
 
7.9%
관계없음 44
 
4.2%
석사과정 16
 
1.5%
무학력 13
 
1.2%
박사과정 3
 
0.3%

희망근무지역(시도)_1
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
서울
1014 
경기
 
18
<NA>
 
16
충남
 
1
경북
 
1
Other values (3)
 
3

Length

Max length4
Median length2
Mean length2.0322887
Min length2

Unique

Unique5 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
서울 1014
96.3%
경기 18
 
1.7%
<NA> 16
 
1.5%
충남 1
 
0.1%
경북 1
 
0.1%
충북 1
 
0.1%
지역무관 1
 
0.1%
인천 1
 
0.1%

Length

2024-05-04T03:26:20.585325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:26:20.801182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울 1014
96.3%
경기 18
 
1.7%
na 16
 
1.5%
충남 1
 
0.1%
경북 1
 
0.1%
충북 1
 
0.1%
지역무관 1
 
0.1%
인천 1
 
0.1%

희망근무지역명(시군구)_1
Categorical

Distinct39
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
<NA>
145 
강남구
74 
노원구
68 
강서구
 
53
중랑구
 
49
Other values (34)
664 

Length

Max length4
Median length3
Mean length3.1994302
Min length2

Unique

Unique9 ?
Unique (%)0.9%

Sample

1st row종로구
2nd row관악구
3rd row강남구
4th row노원구
5th row강남구

Common Values

ValueCountFrequency (%)
<NA> 145
 
13.8%
강남구 74
 
7.0%
노원구 68
 
6.5%
강서구 53
 
5.0%
중랑구 49
 
4.7%
도봉구 48
 
4.6%
동작구 45
 
4.3%
송파구 44
 
4.2%
양천구 40
 
3.8%
관악구 39
 
3.7%
Other values (29) 448
42.5%

Length

2024-05-04T03:26:21.115986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 145
 
13.8%
강남구 74
 
7.0%
노원구 68
 
6.5%
강서구 53
 
5.0%
중랑구 49
 
4.7%
도봉구 48
 
4.6%
동작구 45
 
4.3%
송파구 44
 
4.2%
양천구 40
 
3.8%
관악구 39
 
3.7%
Other values (29) 448
42.5%

희망근무지역명(시도)_2
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
서울
711 
<NA>
250 
경기
 
67
지역무관
 
17
인천
 
4
Other values (4)
 
4

Length

Max length4
Median length2
Mean length2.5071225
Min length2

Unique

Unique4 ?
Unique (%)0.4%

Sample

1st row서울
2nd row<NA>
3rd row서울
4th row서울
5th row서울

Common Values

ValueCountFrequency (%)
서울 711
67.5%
<NA> 250
 
23.7%
경기 67
 
6.4%
지역무관 17
 
1.6%
인천 4
 
0.4%
충남 1
 
0.1%
세종 1
 
0.1%
충북 1
 
0.1%
대전 1
 
0.1%

Length

2024-05-04T03:26:21.484499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:26:21.701364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울 711
67.5%
na 250
 
23.7%
경기 67
 
6.4%
지역무관 17
 
1.6%
인천 4
 
0.4%
충남 1
 
0.1%
세종 1
 
0.1%
충북 1
 
0.1%
대전 1
 
0.1%

희망근무지역명(시군구)_2
Categorical

Distinct45
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
<NA>
663 
전체
 
42
강남구
 
31
송파구
 
21
서초구
 
20
Other values (40)
276 

Length

Max length4
Median length4
Mean length3.6353276
Min length2

Unique

Unique10 ?
Unique (%)0.9%

Sample

1st row<NA>
2nd row<NA>
3rd row서초구
4th row<NA>
5th row서초구

Common Values

ValueCountFrequency (%)
<NA> 663
63.0%
전체 42
 
4.0%
강남구 31
 
2.9%
송파구 21
 
2.0%
서초구 20
 
1.9%
강서구 20
 
1.9%
영등포구 18
 
1.7%
지역무관 17
 
1.6%
양천구 17
 
1.6%
강동구 15
 
1.4%
Other values (35) 189
 
17.9%

Length

2024-05-04T03:26:22.058426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 663
63.0%
전체 42
 
4.0%
강남구 31
 
2.9%
송파구 21
 
2.0%
서초구 20
 
1.9%
강서구 20
 
1.9%
영등포구 18
 
1.7%
지역무관 17
 
1.6%
양천구 17
 
1.6%
강동구 15
 
1.4%
Other values (35) 189
 
17.9%

희망직종공통코드
Real number (ℝ)

Distinct212
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean476386.1
Minimum12204
Maximum905002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2024-05-04T03:26:22.495375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12204
5-th percentile26303.8
Q1531205
median550104
Q3561101
95-th percentile706000
Maximum905002
Range892798
Interquartile range (IQR)29896

Descriptive statistics

Standard deviation210433.21
Coefficient of variation (CV)0.44172827
Kurtosis0.48615266
Mean476386.1
Median Absolute Deviation (MAD)10997
Skewness-1.0099363
Sum5.0163456 × 108
Variance4.4282135 × 1010
MonotonicityNot monotonic
2024-05-04T03:26:22.901686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
550104 167
 
15.9%
561101 147
 
14.0%
561100 71
 
6.7%
542002 65
 
6.2%
542000 28
 
2.7%
542001 28
 
2.7%
562300 25
 
2.4%
550103 25
 
2.4%
561201 18
 
1.7%
29505 17
 
1.6%
Other values (202) 462
43.9%
ValueCountFrequency (%)
12204 2
0.2%
12300 1
 
0.1%
13400 2
0.2%
13903 3
0.3%
14101 1
 
0.1%
14300 1
 
0.1%
14302 2
0.2%
21000 1
 
0.1%
22100 1
 
0.1%
24101 1
 
0.1%
ValueCountFrequency (%)
905002 2
 
0.2%
905001 1
 
0.1%
903900 1
 
0.1%
901502 1
 
0.1%
901500 3
 
0.3%
901400 1
 
0.1%
890007 5
0.5%
890000 9
0.9%
885900 4
0.4%
884200 1
 
0.1%

희망직종공통코드명
Text

Distinct212
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
2024-05-04T03:26:23.465274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length14.149098
Min length2

Characters and Unicode

Total characters14899
Distinct characters296
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

Unique122 ?
Unique (%)11.6%

Sample

1st row음료 조리사(바리스타 포함)
2nd row재가 요양보호사
3rd row아동 생활지도원
4th row기타 사회복지 종사원
5th row보건?의료 관리자(부서장)
ValueCountFrequency (%)
건물 227
 
8.6%
등 225
 
8.6%
재가 167
 
6.4%
요양보호사 167
 
6.4%
청소원(공공건물,아파트,사무실,병원,상가,공장 147
 
5.6%
및 78
 
3.0%
청소원 71
 
2.7%
경비원(청사,학교,병원,상가,빌딩,공장 65
 
2.5%
사무원 60
 
2.3%
기타 50
 
1.9%
Other values (341) 1371
52.2%
2024-05-04T03:26:24.276091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1576
 
10.6%
, 1087
 
7.3%
원 1014
 
6.8%
사 726
 
4.9%
공 608
 
4.1%
건 429
 
2.9%
물 419
 
2.8%
) 409
 
2.7%
( 409
 
2.7%
가 405
 
2.7%
Other values (286) 7817
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11208
75.2%
Space Separator 1576
 
10.6%
Other Punctuation 1276
 
8.6%
Close Punctuation 409
 
2.7%
Open Punctuation 409
 
2.7%
Uppercase Letter 11
 
0.1%
Lowercase Letter 9
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1014
 
9.0%
사 726
 
6.5%
공 608
 
5.4%
건 429
 
3.8%
물 419
 
3.7%
가 405
 
3.6%
보 312
 
2.8%
청 287
 
2.6%
무 273
 
2.4%
장 250
 
2.2%
Other values (264) 6485
57.9%
Uppercase Letter
ValueCountFrequency (%)
A 3
27.3%
S 2
18.2%
T 2
18.2%
C 1
 
9.1%
V 1
 
9.1%
F 1
 
9.1%
M 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
n 2
22.2%
g 1
11.1%
i 1
11.1%
r 1
11.1%
a 1
11.1%
l 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 1087
85.2%
? 187
 
14.7%
/ 1
 
0.1%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1576
100.0%
Close Punctuation
ValueCountFrequency (%)
) 409
100.0%
Open Punctuation
ValueCountFrequency (%)
( 409
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11208
75.2%
Common 3671
 
24.6%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1014
 
9.0%
사 726
 
6.5%
공 608
 
5.4%
건 429
 
3.8%
물 419
 
3.7%
가 405
 
3.6%
보 312
 
2.8%
청 287
 
2.6%
무 273
 
2.4%
장 250
 
2.2%
Other values (264) 6485
57.9%
Latin
ValueCountFrequency (%)
A 3
15.0%
e 2
10.0%
S 2
10.0%
T 2
10.0%
n 2
10.0%
g 1
 
5.0%
C 1
 
5.0%
i 1
 
5.0%
r 1
 
5.0%
V 1
 
5.0%
Other values (4) 4
20.0%
Common
ValueCountFrequency (%)
1576
42.9%
, 1087
29.6%
) 409
 
11.1%
( 409
 
11.1%
? 187
 
5.1%
/ 1
 
< 0.1%
- 1
 
< 0.1%
& 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11208
75.2%
ASCII 3691
 
24.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1576
42.7%
, 1087
29.5%
) 409
 
11.1%
( 409
 
11.1%
? 187
 
5.1%
A 3
 
0.1%
e 2
 
0.1%
S 2
 
0.1%
T 2
 
0.1%
n 2
 
0.1%
Other values (12) 12
 
0.3%
Hangul
ValueCountFrequency (%)
원 1014
 
9.0%
사 726
 
6.5%
공 608
 
5.4%
건 429
 
3.8%
물 419
 
3.7%
가 405
 
3.6%
보 312
 
2.8%
청 287
 
2.6%
무 273
 
2.4%
장 250
 
2.2%
Other values (264) 6485
57.9%

희망직종경력년수
Real number (ℝ)

MISSING  ZEROS 

Distinct34
Distinct (%)5.5%
Missing433
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean6.3564516
Minimum0
Maximum42
Zeros102
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2024-05-04T03:26:24.680234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3.5
Q310
95-th percentile23.1
Maximum42
Range42
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.5416157
Coefficient of variation (CV)1.1864506
Kurtosis3.44736
Mean6.3564516
Median Absolute Deviation (MAD)3.5
Skewness1.8556777
Sum3941
Variance56.875968
MonotonicityNot monotonic
2024-05-04T03:26:25.070740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 102
 
9.7%
1 81
 
7.7%
2 68
 
6.5%
3 59
 
5.6%
10 52
 
4.9%
5 50
 
4.7%
4 30
 
2.8%
7 28
 
2.7%
20 25
 
2.4%
6 21
 
2.0%
Other values (24) 104
 
9.9%
(Missing) 433
41.1%
ValueCountFrequency (%)
0 102
9.7%
1 81
7.7%
2 68
6.5%
3 59
5.6%
4 30
 
2.8%
5 50
4.7%
6 21
 
2.0%
7 28
 
2.7%
8 15
 
1.4%
9 9
 
0.9%
ValueCountFrequency (%)
42 1
 
0.1%
40 1
 
0.1%
36 1
 
0.1%
35 1
 
0.1%
34 1
 
0.1%
31 1
 
0.1%
30 13
1.2%
29 1
 
0.1%
28 2
 
0.2%
27 1
 
0.1%

희망직종경력개월수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.9%
Missing433
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean1.3806452
Minimum0
Maximum11
Zeros461
Zeros (%)43.8%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2024-05-04T03:26:25.421167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8
Maximum11
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.694507
Coefficient of variation (CV)1.9516289
Kurtosis2.3278644
Mean1.3806452
Median Absolute Deviation (MAD)0
Skewness1.8607141
Sum856
Variance7.2603679
MonotonicityNot monotonic
2024-05-04T03:26:25.761260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 461
43.8%
6 38
 
3.6%
3 20
 
1.9%
5 19
 
1.8%
4 17
 
1.6%
8 13
 
1.2%
2 12
 
1.1%
9 11
 
1.0%
1 11
 
1.0%
10 7
 
0.7%
Other values (2) 11
 
1.0%
(Missing) 433
41.1%
ValueCountFrequency (%)
0 461
43.8%
1 11
 
1.0%
2 12
 
1.1%
3 20
 
1.9%
4 17
 
1.6%
5 19
 
1.8%
6 38
 
3.6%
7 6
 
0.6%
8 13
 
1.2%
9 11
 
1.0%
ValueCountFrequency (%)
11 5
 
0.5%
10 7
 
0.7%
9 11
 
1.0%
8 13
 
1.2%
7 6
 
0.6%
6 38
3.6%
5 19
1.8%
4 17
1.6%
3 20
1.9%
2 12
 
1.1%

희망직종경력년_월수
Text

Distinct109
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
2024-05-04T03:26:26.266580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.2602089
Min length2

Characters and Unicode

Total characters3433
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)5.9%

Sample

1st row신입
2nd row5년0월
3rd row신입
4th row신입
5th row1년0월
ValueCountFrequency (%)
신입 474
45.0%
1년0월 55
 
5.2%
2년0월 53
 
5.0%
3년0월 51
 
4.8%
10년0월 47
 
4.5%
5년0월 44
 
4.2%
7년0월 23
 
2.2%
20년0월 22
 
2.1%
4년0월 21
 
2.0%
6년0월 18
 
1.7%
Other values (99) 245
23.3%
2024-05-04T03:26:27.148991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
년 579
16.9%
0 579
16.9%
월 579
16.9%
신 474
13.8%
입 474
13.8%
1 213
 
6.2%
2 129
 
3.8%
3 103
 
3.0%
5 89
 
2.6%
6 63
 
1.8%
Other values (4) 151
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2106
61.3%
Decimal Number 1327
38.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 579
43.6%
1 213
 
16.1%
2 129
 
9.7%
3 103
 
7.8%
5 89
 
6.7%
6 63
 
4.7%
4 58
 
4.4%
7 37
 
2.8%
8 33
 
2.5%
9 23
 
1.7%
Other Letter
ValueCountFrequency (%)
년 579
27.5%
월 579
27.5%
신 474
22.5%
입 474
22.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2106
61.3%
Common 1327
38.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 579
43.6%
1 213
 
16.1%
2 129
 
9.7%
3 103
 
7.8%
5 89
 
6.7%
6 63
 
4.7%
4 58
 
4.4%
7 37
 
2.8%
8 33
 
2.5%
9 23
 
1.7%
Hangul
ValueCountFrequency (%)
년 579
27.5%
월 579
27.5%
신 474
22.5%
입 474
22.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2106
61.3%
ASCII 1327
38.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
년 579
27.5%
월 579
27.5%
신 474
22.5%
입 474
22.5%
ASCII
ValueCountFrequency (%)
0 579
43.6%
1 213
 
16.1%
2 129
 
9.7%
3 103
 
7.8%
5 89
 
6.7%
6 63
 
4.7%
4 58
 
4.4%
7 37
 
2.8%
8 33
 
2.5%
9 23
 
1.7%

구직인증상태공통구분
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
J03402
714 
J03404
329 
J03405
 
10

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJ03402
2nd rowJ03402
3rd rowJ03404
4th rowJ03402
5th rowJ03402

Common Values

ValueCountFrequency (%)
J03402 714
67.8%
J03404 329
31.2%
J03405 10
 
0.9%

Length

2024-05-04T03:26:27.547826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:26:27.771321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
j03402 714
67.8%
j03404 329
31.2%
j03405 10
 
0.9%

구직인증상태공통구분명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
승인
714 
알선
329 
알선대기
 
10

Length

Max length4
Median length2
Mean length2.0189934
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row승인
2nd row승인
3rd row알선
4th row승인
5th row승인

Common Values

ValueCountFrequency (%)
승인 714
67.8%
알선 329
31.2%
알선대기 10
 
0.9%

Length

2024-05-04T03:26:28.143901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:26:28.472954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승인 714
67.8%
알선 329
31.2%
알선대기 10
 
0.9%

검색키워드1
Text

MISSING 

Distinct112
Distinct (%)77.2%
Missing908
Missing (%)86.2%
Memory size8.4 KiB
2024-05-04T03:26:28.969913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length4.4344828
Min length1

Characters and Unicode

Total characters643
Distinct characters180
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)65.5%

Sample

1st row청소
2nd row양평
3rd row석션
4th row컴퓨터 설치?수리원
5th row동대문구
ValueCountFrequency (%)
동대문구 8
 
4.4%
경비 7
 
3.8%
오후 5
 
2.7%
청소 5
 
2.7%
아파트 4
 
2.2%
사무원 3
 
1.6%
건물 3
 
1.6%
복지카드 3
 
1.6%
경리 3
 
1.6%
석션 2
 
1.1%
Other values (123) 140
76.5%
2024-05-04T03:26:30.167548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
6.1%
원 22
 
3.4%
사 22
 
3.4%
경 17
 
2.6%
비 14
 
2.2%
리 14
 
2.2%
. 14
 
2.2%
동 13
 
2.0%
청 13
 
2.0%
소 13
 
2.0%
Other values (170) 462
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 565
87.9%
Space Separator 39
 
6.1%
Other Punctuation 22
 
3.4%
Decimal Number 11
 
1.7%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 22
 
3.9%
사 22
 
3.9%
경 17
 
3.0%
비 14
 
2.5%
리 14
 
2.5%
동 13
 
2.3%
청 13
 
2.3%
소 13
 
2.3%
대 12
 
2.1%
문 11
 
1.9%
Other values (159) 414
73.3%
Decimal Number
ValueCountFrequency (%)
2 4
36.4%
4 2
18.2%
5 2
18.2%
3 2
18.2%
1 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 14
63.6%
, 4
 
18.2%
? 4
 
18.2%
Space Separator
ValueCountFrequency (%)
39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 565
87.9%
Common 78
 
12.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 22
 
3.9%
사 22
 
3.9%
경 17
 
3.0%
비 14
 
2.5%
리 14
 
2.5%
동 13
 
2.3%
청 13
 
2.3%
소 13
 
2.3%
대 12
 
2.1%
문 11
 
1.9%
Other values (159) 414
73.3%
Common
ValueCountFrequency (%)
39
50.0%
. 14
 
17.9%
, 4
 
5.1%
? 4
 
5.1%
2 4
 
5.1%
( 3
 
3.8%
) 3
 
3.8%
4 2
 
2.6%
5 2
 
2.6%
3 2
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 565
87.9%
ASCII 78
 
12.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
50.0%
. 14
 
17.9%
, 4
 
5.1%
? 4
 
5.1%
2 4
 
5.1%
( 3
 
3.8%
) 3
 
3.8%
4 2
 
2.6%
5 2
 
2.6%
3 2
 
2.6%
Hangul
ValueCountFrequency (%)
원 22
 
3.9%
사 22
 
3.9%
경 17
 
3.0%
비 14
 
2.5%
리 14
 
2.5%
동 13
 
2.3%
청 13
 
2.3%
소 13
 
2.3%
대 12
 
2.1%
문 11
 
1.9%
Other values (159) 414
73.3%

검색키워드2
Text

MISSING 

Distinct97
Distinct (%)84.3%
Missing938
Missing (%)89.1%
Memory size8.4 KiB
2024-05-04T03:26:30.722132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length4.026087
Min length1

Characters and Unicode

Total characters463
Distinct characters165
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)73.0%

Sample

1st row미화
2nd row당산
3rd row피딩
4th row보안 관제원
5th row요양
ValueCountFrequency (%)
청소 5
 
3.7%
경비원 4
 
3.0%
경비 3
 
2.2%
요양보호사 3
 
2.2%
사무원 2
 
1.5%
기계 2
 
1.5%
운전2종보통 2
 
1.5%
청소원 2
 
1.5%
콘텐츠 2
 
1.5%
건물 2
 
1.5%
Other values (103) 107
79.9%
2024-05-04T03:26:31.705160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
4.1%
원 17
 
3.7%
비 16
 
3.5%
경 14
 
3.0%
사 14
 
3.0%
보 12
 
2.6%
청 11
 
2.4%
교 10
 
2.2%
전 9
 
1.9%
소 9
 
1.9%
Other values (155) 332
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 424
91.6%
Space Separator 19
 
4.1%
Other Punctuation 11
 
2.4%
Decimal Number 6
 
1.3%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 17
 
4.0%
비 16
 
3.8%
경 14
 
3.3%
사 14
 
3.3%
보 12
 
2.8%
청 11
 
2.6%
교 10
 
2.4%
전 9
 
2.1%
소 9
 
2.1%
무 8
 
1.9%
Other values (143) 304
71.7%
Other Punctuation
ValueCountFrequency (%)
. 8
72.7%
/ 1
 
9.1%
? 1
 
9.1%
, 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
5 2
33.3%
2 2
33.3%
1 1
16.7%
6 1
16.7%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 424
91.6%
Common 38
 
8.2%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 17
 
4.0%
비 16
 
3.8%
경 14
 
3.3%
사 14
 
3.3%
보 12
 
2.8%
청 11
 
2.6%
교 10
 
2.4%
전 9
 
2.1%
소 9
 
2.1%
무 8
 
1.9%
Other values (143) 304
71.7%
Common
ValueCountFrequency (%)
19
50.0%
. 8
21.1%
5 2
 
5.3%
2 2
 
5.3%
1 1
 
2.6%
6 1
 
2.6%
/ 1
 
2.6%
) 1
 
2.6%
( 1
 
2.6%
? 1
 
2.6%
Latin
ValueCountFrequency (%)
x 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 424
91.6%
ASCII 39
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
48.7%
. 8
20.5%
5 2
 
5.1%
2 2
 
5.1%
1 1
 
2.6%
6 1
 
2.6%
/ 1
 
2.6%
) 1
 
2.6%
( 1
 
2.6%
? 1
 
2.6%
Other values (2) 2
 
5.1%
Hangul
ValueCountFrequency (%)
원 17
 
4.0%
비 16
 
3.8%
경 14
 
3.3%
사 14
 
3.3%
보 12
 
2.8%
청 11
 
2.6%
교 10
 
2.4%
전 9
 
2.1%
소 9
 
2.1%
무 8
 
1.9%
Other values (143) 304
71.7%

검색키워드3
Text

MISSING 

Distinct73
Distinct (%)90.1%
Missing972
Missing (%)92.3%
Memory size8.4 KiB
2024-05-04T03:26:32.372610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length4.4197531
Min length1

Characters and Unicode

Total characters358
Distinct characters142
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)81.5%

Sample

1st row요양보호사
2nd row문래
3rd row박물관,미술관,문화,역사,자연환경 등 각종 해설사
4th row베이비시터
5th row숙박
ValueCountFrequency (%)
청소 3
 
3.0%
영선 2
 
2.0%
미화 2
 
2.0%
오전 2
 
2.0%
이태원 2
 
2.0%
경비 2
 
2.0%
제조 2
 
2.0%
문래 2
 
2.0%
복지카드 2
 
2.0%
설비 1
 
1.0%
Other values (79) 79
79.8%
2024-05-04T03:26:33.278256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
5.0%
사 12
 
3.4%
원 11
 
3.1%
관 8
 
2.2%
, 7
 
2.0%
보 7
 
2.0%
비 7
 
2.0%
물 6
 
1.7%
경 6
 
1.7%
청 6
 
1.7%
Other values (132) 270
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
88.5%
Space Separator 18
 
5.0%
Other Punctuation 14
 
3.9%
Uppercase Letter 6
 
1.7%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%
Lowercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 12
 
3.8%
원 11
 
3.5%
관 8
 
2.5%
보 7
 
2.2%
비 7
 
2.2%
물 6
 
1.9%
경 6
 
1.9%
청 6
 
1.9%
전 6
 
1.9%
이 5
 
1.6%
Other values (119) 243
76.7%
Uppercase Letter
ValueCountFrequency (%)
Q 1
16.7%
S 1
16.7%
M 1
16.7%
L 1
16.7%
D 1
16.7%
B 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 7
50.0%
? 5
35.7%
. 2
 
14.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
88.5%
Common 34
 
9.5%
Latin 7
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 12
 
3.8%
원 11
 
3.5%
관 8
 
2.5%
보 7
 
2.2%
비 7
 
2.2%
물 6
 
1.9%
경 6
 
1.9%
청 6
 
1.9%
전 6
 
1.9%
이 5
 
1.6%
Other values (119) 243
76.7%
Latin
ValueCountFrequency (%)
Q 1
14.3%
S 1
14.3%
y 1
14.3%
M 1
14.3%
L 1
14.3%
D 1
14.3%
B 1
14.3%
Common
ValueCountFrequency (%)
18
52.9%
, 7
 
20.6%
? 5
 
14.7%
. 2
 
5.9%
) 1
 
2.9%
( 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
88.5%
ASCII 41
 
11.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
43.9%
, 7
 
17.1%
? 5
 
12.2%
. 2
 
4.9%
) 1
 
2.4%
( 1
 
2.4%
Q 1
 
2.4%
S 1
 
2.4%
y 1
 
2.4%
M 1
 
2.4%
Other values (3) 3
 
7.3%
Hangul
ValueCountFrequency (%)
사 12
 
3.8%
원 11
 
3.5%
관 8
 
2.5%
보 7
 
2.2%
비 7
 
2.2%
물 6
 
1.9%
경 6
 
1.9%
청 6
 
1.9%
전 6
 
1.9%
이 5
 
1.6%
Other values (119) 243
76.7%

검색키워드4
Text

MISSING 

Distinct53
Distinct (%)93.0%
Missing996
Missing (%)94.6%
Memory size8.4 KiB
2024-05-04T03:26:33.774044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.2807018
Min length1

Characters and Unicode

Total characters187
Distinct characters112
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

Unique49 ?
Unique (%)86.0%

Sample

1st row환경 감시원
2nd row컴퓨터
3rd row보안
4th row단순
5th row주차장
ValueCountFrequency (%)
단순 3
 
4.7%
외곽 2
 
3.1%
장안 2
 
3.1%
오전 2
 
3.1%
운전 2
 
3.1%
일본인안내 1
 
1.6%
교육 1
 
1.6%
주차장 1
 
1.6%
용접 1
 
1.6%
러시아어 1
 
1.6%
Other values (48) 48
75.0%
2024-05-04T03:26:34.699892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
3.7%
사 6
 
3.2%
안 6
 
3.2%
전 5
 
2.7%
교 4
 
2.1%
장 4
 
2.1%
영 4
 
2.1%
육 4
 
2.1%
차 3
 
1.6%
내 3
 
1.6%
Other values (102) 141
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 172
92.0%
Space Separator 7
 
3.7%
Uppercase Letter 4
 
2.1%
Other Punctuation 3
 
1.6%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 6
 
3.5%
안 6
 
3.5%
전 5
 
2.9%
교 4
 
2.3%
장 4
 
2.3%
영 4
 
2.3%
육 4
 
2.3%
차 3
 
1.7%
내 3
 
1.7%
리 3
 
1.7%
Other values (95) 130
75.6%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
J 1
25.0%
V 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 172
92.0%
Common 11
 
5.9%
Latin 4
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 6
 
3.5%
안 6
 
3.5%
전 5
 
2.9%
교 4
 
2.3%
장 4
 
2.3%
영 4
 
2.3%
육 4
 
2.3%
차 3
 
1.7%
내 3
 
1.7%
리 3
 
1.7%
Other values (95) 130
75.6%
Common
ValueCountFrequency (%)
7
63.6%
. 2
 
18.2%
, 1
 
9.1%
4 1
 
9.1%
Latin
ValueCountFrequency (%)
A 2
50.0%
J 1
25.0%
V 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 172
92.0%
ASCII 15
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
46.7%
A 2
 
13.3%
. 2
 
13.3%
J 1
 
6.7%
V 1
 
6.7%
, 1
 
6.7%
4 1
 
6.7%
Hangul
ValueCountFrequency (%)
사 6
 
3.5%
안 6
 
3.5%
전 5
 
2.9%
교 4
 
2.3%
장 4
 
2.3%
영 4
 
2.3%
육 4
 
2.3%
차 3
 
1.7%
내 3
 
1.7%
리 3
 
1.7%
Other values (95) 130
75.6%

검색키워드5
Text

MISSING 

Distinct37
Distinct (%)97.4%
Missing1015
Missing (%)96.4%
Memory size8.4 KiB
2024-05-04T03:26:35.141809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.4473684
Min length1

Characters and Unicode

Total characters131
Distinct characters91
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)94.7%

Sample

1st row단순직
2nd row디자인
3rd row성실
4th row전기
5th row강서
ValueCountFrequency (%)
전농 2
 
4.8%
경비 2
 
4.8%
평생교육 1
 
2.4%
및 1
 
2.4%
마케팅 1
 
2.4%
일본인가이드 1
 
2.4%
긴시간 1
 
2.4%
신촌 1
 
2.4%
답십리 1
 
2.4%
오피스텔청소 1
 
2.4%
Other values (30) 30
71.4%
2024-05-04T03:26:36.084682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 5
 
3.8%
전 4
 
3.1%
4
 
3.1%
인 4
 
3.1%
관 4
 
3.1%
보 3
 
2.3%
이 2
 
1.5%
비 2
 
1.5%
당 2
 
1.5%
산 2
 
1.5%
Other values (81) 99
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
94.7%
Space Separator 4
 
3.1%
Other Punctuation 2
 
1.5%
Decimal Number 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 5
 
4.0%
전 4
 
3.2%
인 4
 
3.2%
관 4
 
3.2%
보 3
 
2.4%
이 2
 
1.6%
비 2
 
1.6%
당 2
 
1.6%
산 2
 
1.6%
마 2
 
1.6%
Other values (77) 94
75.8%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
94.7%
Common 7
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 5
 
4.0%
전 4
 
3.2%
인 4
 
3.2%
관 4
 
3.2%
보 3
 
2.4%
이 2
 
1.6%
비 2
 
1.6%
당 2
 
1.6%
산 2
 
1.6%
마 2
 
1.6%
Other values (77) 94
75.8%
Common
ValueCountFrequency (%)
4
57.1%
. 1
 
14.3%
2 1
 
14.3%
, 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124
94.7%
ASCII 7
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 5
 
4.0%
전 4
 
3.2%
인 4
 
3.2%
관 4
 
3.2%
보 3
 
2.4%
이 2
 
1.6%
비 2
 
1.6%
당 2
 
1.6%
산 2
 
1.6%
마 2
 
1.6%
Other values (77) 94
75.8%
ASCII
ValueCountFrequency (%)
4
57.1%
. 1
 
14.3%
2 1
 
14.3%
, 1
 
14.3%

등록일시
Date

Distinct1050
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
Minimum2024-01-05 21:07:43
Maximum2024-05-03 17:47:50
2024-05-04T03:26:36.477606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:26:36.905522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

Distinct1043
Distinct (%)99.1%
Missing1
Missing (%)0.1%
Memory size8.4 KiB
Minimum2024-05-01 07:47:56
Maximum2024-05-03 21:33:28
2024-05-04T03:26:37.316117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:26:37.718298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Sample

구직신청번호성별나이학력공통코드학력공통코드명희망근무지역(시도)_1희망근무지역명(시군구)_1희망근무지역명(시도)_2희망근무지역명(시군구)_2희망직종공통코드희망직종공통코드명희망직종경력년수희망직종경력개월수희망직종경력년_월수구직인증상태공통구분구직인증상태공통구분명검색키워드1검색키워드2검색키워드3검색키워드4검색키워드5등록일시수정일시
0H301202405032563여18J00100관계없음서울종로구서울<NA>531700음료 조리사(바리스타 포함)<NA><NA>신입J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:47:50.02024-05-03 17:47:55.0
1H321202405032562여65J00106고등학교서울관악구<NA><NA>550104재가 요양보호사505년0월J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:47:18.02024-05-03 18:01:42.0
2H323202405032561여64J00110대학_대학교서울강남구서울서초구232902아동 생활지도원<NA><NA>신입J03404알선<NA><NA><NA><NA><NA>2024-05-03 17:45:31.02024-05-03 17:45:36.0
3H311202405032547여62J00108전문대학서울노원구서울<NA>232900기타 사회복지 종사원<NA><NA>신입J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:40:22.02024-05-03 17:40:27.0
4H322202405032546여64J00108전문대학서울강남구서울서초구13400보건?의료 관리자(부서장)101년0월J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:39:09.02024-05-03 17:39:13.0
5H316202405032518남53J00110대학_대학교서울전체경기전체29902출판?자료 편집 사무원20020년0월J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:30:10.02024-05-03 17:41:42.0
6H301202405032517여24J00100관계없음서울종로구서울<NA>531700음료 조리사(바리스타 포함)<NA><NA>신입J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:27:41.02024-05-03 17:27:47.0
7H316202405032503남59J00106고등학교서울강서구서울양천구615103편의점 판매원505년0월J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:25:25.02024-05-03 17:25:31.0
8H316202405032467여71J00104중학교서울강서구<NA><NA>532301주방 보조원(일반 음식점)101년0월J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:15:57.02024-05-03 17:16:01.0
9H310202405032465남59J00110대학_대학교서울도봉구서울<NA>834002빌딩 전기관리원<NA><NA>신입J03402승인<NA><NA><NA><NA><NA>2024-05-03 17:15:41.02024-05-03 17:15:47.0
구직신청번호성별나이학력공통코드학력공통코드명희망근무지역(시도)_1희망근무지역명(시군구)_1희망근무지역명(시도)_2희망근무지역명(시군구)_2희망직종공통코드희망직종공통코드명희망직종경력년수희망직종경력개월수희망직종경력년_월수구직인증상태공통구분구직인증상태공통구분명검색키워드1검색키워드2검색키워드3검색키워드4검색키워드5등록일시수정일시
1043H321202402260446남71J00102초등학교서울관악구서울전체561101건물 청소원(공공건물,아파트,사무실,병원,상가,공장 등)202년0월J03404알선<NA><NA><NA><NA><NA>2024-02-26 10:25:36.02024-05-03 12:00:50.0
1044H001202402231961남60J00112석사과정인천전체경기부천시231101사회복지사(사회복지시설)26026년0월J03404알선<NA><NA><NA><NA><NA>2024-02-23 16:38:00.02024-05-03 14:51:33.0
1045H310202402160981여64J00106고등학교서울도봉구서울강북구532202일반 음식점 서빙원10110년1월J03404알선건물 청소원청소원<NA><NA><NA>2024-02-16 12:01:00.02024-05-03 15:46:35.0
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