Overview

Dataset statistics

Number of variables7
Number of observations2328
Missing cells163
Missing cells (%)1.0%
Duplicate rows12
Duplicate rows (%)0.5%
Total size in memory129.7 KiB
Average record size in memory57.1 B

Variable types

Categorical2
Text4
Numeric1

Dataset

Description한국지역난방공사에서 진행되는 안전관리관련 교육실적 정보 (지사, 일자, 대상, 교육내용, 교육인원, 교육시간, 강사)
URLhttps://www.data.go.kr/data/15069218/fileData.do

Alerts

Dataset has 12 (0.5%) duplicate rowsDuplicates
교육시간 is highly imbalanced (62.5%)Imbalance
교육인원 has 163 (7.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 21:35:01.592547
Analysis finished2023-12-12 21:35:02.989233
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지 사
Categorical

Distinct19
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
광교
172 
수원
 
141
분당
 
139
대구
 
138
강남
 
137
Other values (14)
1601 

Length

Max length4
Median length2
Mean length2.0919244
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광교 172
 
7.4%
수원 141
 
6.1%
분당 139
 
6.0%
대구 138
 
5.9%
강남 137
 
5.9%
삼송 134
 
5.8%
파주 131
 
5.6%
화성 129
 
5.5%
양산 129
 
5.5%
용인 128
 
5.5%
Other values (9) 950
40.8%

Length

2023-12-13T06:35:03.081383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광교 172
 
7.4%
수원 141
 
6.1%
분당 139
 
6.0%
대구 138
 
5.9%
강남 137
 
5.9%
삼송 134
 
5.8%
파주 131
 
5.6%
화성 129
 
5.5%
양산 129
 
5.5%
용인 128
 
5.5%
Other values (9) 950
40.8%

일자
Text

Distinct842
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-13T06:35:03.413574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters23280
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

Unique407 ?
Unique (%)17.5%

Sample

1st row2014-01-06
2nd row2014-02-04
3rd row2014-03-03
4th row2014-03-04
5th row2014-03-04
ValueCountFrequency (%)
2014-03-04 18
 
0.8%
2015-09-04 15
 
0.6%
2020-02-04 15
 
0.6%
2019-12-04 15
 
0.6%
2020-06-04 15
 
0.6%
2017-07-04 15
 
0.6%
2017-01-04 15
 
0.6%
2018-07-04 14
 
0.6%
2015-02-04 14
 
0.6%
2015-05-06 14
 
0.6%
Other values (832) 2178
93.6%
2023-12-13T06:35:03.918452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6391
27.5%
- 4656
20.0%
2 4365
18.8%
1 3090
13.3%
4 1151
 
4.9%
3 732
 
3.1%
6 682
 
2.9%
5 681
 
2.9%
7 550
 
2.4%
8 517
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18624
80.0%
Dash Punctuation 4656
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6391
34.3%
2 4365
23.4%
1 3090
16.6%
4 1151
 
6.2%
3 732
 
3.9%
6 682
 
3.7%
5 681
 
3.7%
7 550
 
3.0%
8 517
 
2.8%
9 465
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 4656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6391
27.5%
- 4656
20.0%
2 4365
18.8%
1 3090
13.3%
4 1151
 
4.9%
3 732
 
3.1%
6 682
 
2.9%
5 681
 
2.9%
7 550
 
2.4%
8 517
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6391
27.5%
- 4656
20.0%
2 4365
18.8%
1 3090
13.3%
4 1151
 
4.9%
3 732
 
3.1%
6 682
 
2.9%
5 681
 
2.9%
7 550
 
2.4%
8 517
 
2.2%

대상
Text

Distinct78
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-13T06:35:04.169472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length9.262457
Min length2

Characters and Unicode

Total characters21563
Distinct characters113
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

Unique9 ?
Unique (%)0.4%

Sample

1st row현업원
2nd row현업원
3rd row신규직원
4th row작업변경자
5th row현업원
ValueCountFrequency (%)
협력업체 828
15.7%
및 681
12.9%
직원 594
 
11.2%
우리직원 506
 
9.6%
전직원 272
 
5.2%
지사 260
 
4.9%
우리 161
 
3.0%
외부작업자 127
 
2.4%
한전kps 125
 
2.4%
한난 120
 
2.3%
Other values (54) 1606
30.4%
2023-12-13T06:35:04.574568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2952
13.7%
원 2081
 
9.7%
직 1954
 
9.1%
업 1354
 
6.3%
체 1094
 
5.1%
협 1064
 
4.9%
력 1062
 
4.9%
사 1026
 
4.8%
지 1013
 
4.7%
리 735
 
3.4%
Other values (103) 7228
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16600
77.0%
Space Separator 2952
 
13.7%
Uppercase Letter 890
 
4.1%
Other Punctuation 781
 
3.6%
Decimal Number 322
 
1.5%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 2081
12.5%
직 1954
11.8%
업 1354
 
8.2%
체 1094
 
6.6%
협 1064
 
6.4%
력 1062
 
6.4%
사 1026
 
6.2%
지 1013
 
6.1%
리 735
 
4.4%
우 734
 
4.4%
Other values (84) 4483
27.0%
Uppercase Letter
ValueCountFrequency (%)
S 282
31.7%
P 282
31.7%
K 282
31.7%
N 12
 
1.3%
E 12
 
1.3%
G 12
 
1.3%
T 2
 
0.2%
F 2
 
0.2%
H 2
 
0.2%
O 2
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 618
79.1%
& 103
 
13.2%
/ 60
 
7.7%
Decimal Number
ValueCountFrequency (%)
0 180
55.9%
5 82
25.5%
2 60
 
18.6%
Space Separator
ValueCountFrequency (%)
2952
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16600
77.0%
Common 4073
 
18.9%
Latin 890
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 2081
12.5%
직 1954
11.8%
업 1354
 
8.2%
체 1094
 
6.6%
협 1064
 
6.4%
력 1062
 
6.4%
사 1026
 
6.2%
지 1013
 
6.1%
리 735
 
4.4%
우 734
 
4.4%
Other values (84) 4483
27.0%
Latin
ValueCountFrequency (%)
S 282
31.7%
P 282
31.7%
K 282
31.7%
N 12
 
1.3%
E 12
 
1.3%
G 12
 
1.3%
T 2
 
0.2%
F 2
 
0.2%
H 2
 
0.2%
O 2
 
0.2%
Common
ValueCountFrequency (%)
2952
72.5%
, 618
 
15.2%
0 180
 
4.4%
& 103
 
2.5%
5 82
 
2.0%
/ 60
 
1.5%
2 60
 
1.5%
( 9
 
0.2%
) 9
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16600
77.0%
ASCII 4963
 
23.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2952
59.5%
, 618
 
12.5%
S 282
 
5.7%
P 282
 
5.7%
K 282
 
5.7%
0 180
 
3.6%
& 103
 
2.1%
5 82
 
1.7%
/ 60
 
1.2%
2 60
 
1.2%
Other values (9) 62
 
1.2%
Hangul
ValueCountFrequency (%)
원 2081
12.5%
직 1954
11.8%
업 1354
 
8.2%
체 1094
 
6.6%
협 1064
 
6.4%
력 1062
 
6.4%
사 1026
 
6.2%
지 1013
 
6.1%
리 735
 
4.4%
우 734
 
4.4%
Other values (84) 4483
27.0%

교육내용
Text

Distinct2189
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-13T06:35:04.889912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length291
Median length110
Mean length30.32689
Min length4

Characters and Unicode

Total characters70601
Distinct characters542
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2094 ?
Unique (%)89.9%

Sample

1st row2013 자체감사결과 등
2nd row2014년 재난안전관리 기본계획 화학물질 MSDS 교육등
3rd row신규직원(인사이동)
4th row작업변경자(인사이동)
5th row지사장 교육 및 안전조작 절차
ValueCountFrequency (%)
및 1004
 
6.6%
교육 857
 
5.6%
등 741
 
4.9%
결과 259
 
1.7%
psm 179
 
1.2%
예방 163
 
1.1%
안전교육 162
 
1.1%
위험성평가 150
 
1.0%
근로자 145
 
1.0%
전파교육 123
 
0.8%
Other values (3104) 11471
75.2%
2023-12-13T06:35:05.354153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13244
 
18.8%
전 2686
 
3.8%
안 2371
 
3.4%
교 1909
 
2.7%
육 1866
 
2.6%
사 1693
 
2.4%
, 1273
 
1.8%
및 1008
 
1.4%
보 952
 
1.3%
정 945
 
1.3%
Other values (532) 42654
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49970
70.8%
Space Separator 13244
 
18.8%
Decimal Number 2201
 
3.1%
Uppercase Letter 1961
 
2.8%
Other Punctuation 1584
 
2.2%
Open Punctuation 603
 
0.9%
Close Punctuation 602
 
0.9%
Lowercase Letter 324
 
0.5%
Dash Punctuation 46
 
0.1%
Other Number 21
 
< 0.1%
Other values (4) 45
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 2686
 
5.4%
안 2371
 
4.7%
교 1909
 
3.8%
육 1866
 
3.7%
사 1693
 
3.4%
및 1008
 
2.0%
보 952
 
1.9%
정 945
 
1.9%
기 936
 
1.9%
관 884
 
1.8%
Other values (447) 34720
69.5%
Uppercase Letter
ValueCountFrequency (%)
S 602
30.7%
M 430
21.9%
P 344
17.5%
D 149
 
7.6%
A 57
 
2.9%
O 51
 
2.6%
T 49
 
2.5%
C 45
 
2.3%
F 35
 
1.8%
H 34
 
1.7%
Other values (14) 165
 
8.4%
Lowercase Letter
ValueCountFrequency (%)
t 42
13.0%
e 40
12.3%
o 34
10.5%
a 26
 
8.0%
n 25
 
7.7%
i 22
 
6.8%
r 15
 
4.6%
f 14
 
4.3%
y 12
 
3.7%
c 11
 
3.4%
Other values (12) 83
25.6%
Decimal Number
ValueCountFrequency (%)
2 900
40.9%
0 438
19.9%
1 428
19.4%
3 114
 
5.2%
4 85
 
3.9%
9 70
 
3.2%
6 50
 
2.3%
8 44
 
2.0%
5 39
 
1.8%
7 33
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 1273
80.4%
/ 208
 
13.1%
· 49
 
3.1%
' 18
 
1.1%
. 14
 
0.9%
: 11
 
0.7%
# 8
 
0.5%
& 3
 
0.2%
Other Number
ValueCountFrequency (%)
② 5
23.8%
① 5
23.8%
④ 4
19.0%
③ 4
19.0%
⑦ 1
 
4.8%
⑥ 1
 
4.8%
⑤ 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 526
87.2%
[ 49
 
8.1%
「 28
 
4.6%
Close Punctuation
ValueCountFrequency (%)
) 525
87.2%
] 49
 
8.1%
」 28
 
4.7%
Math Symbol
ValueCountFrequency (%)
~ 14
87.5%
+ 1
 
6.2%
| 1
 
6.2%
Space Separator
ValueCountFrequency (%)
13244
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 10
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49970
70.8%
Common 18346
 
26.0%
Latin 2285
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 2686
 
5.4%
안 2371
 
4.7%
교 1909
 
3.8%
육 1866
 
3.7%
사 1693
 
3.4%
및 1008
 
2.0%
보 952
 
1.9%
정 945
 
1.9%
기 936
 
1.9%
관 884
 
1.8%
Other values (447) 34720
69.5%
Latin
ValueCountFrequency (%)
S 602
26.3%
M 430
18.8%
P 344
15.1%
D 149
 
6.5%
A 57
 
2.5%
O 51
 
2.2%
T 49
 
2.1%
C 45
 
2.0%
t 42
 
1.8%
e 40
 
1.8%
Other values (36) 476
20.8%
Common
ValueCountFrequency (%)
13244
72.2%
, 1273
 
6.9%
2 900
 
4.9%
( 526
 
2.9%
) 525
 
2.9%
0 438
 
2.4%
1 428
 
2.3%
/ 208
 
1.1%
3 114
 
0.6%
4 85
 
0.5%
Other values (29) 605
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49966
70.8%
ASCII 20486
29.0%
None 105
 
0.1%
Enclosed Alphanum 21
 
< 0.1%
Punctuation 19
 
< 0.1%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13244
64.6%
, 1273
 
6.2%
2 900
 
4.4%
S 602
 
2.9%
( 526
 
2.6%
) 525
 
2.6%
0 438
 
2.1%
M 430
 
2.1%
1 428
 
2.1%
P 344
 
1.7%
Other values (63) 1776
 
8.7%
Hangul
ValueCountFrequency (%)
전 2686
 
5.4%
안 2371
 
4.7%
교 1909
 
3.8%
육 1866
 
3.7%
사 1693
 
3.4%
및 1008
 
2.0%
보 952
 
1.9%
정 945
 
1.9%
기 936
 
1.9%
관 884
 
1.8%
Other values (444) 34716
69.5%
None
ValueCountFrequency (%)
· 49
46.7%
」 28
26.7%
「 28
26.7%
Punctuation
ValueCountFrequency (%)
‘ 13
68.4%
’ 6
31.6%
Enclosed Alphanum
ValueCountFrequency (%)
② 5
23.8%
① 5
23.8%
④ 4
19.0%
③ 4
19.0%
⑦ 1
 
4.8%
⑥ 1
 
4.8%
⑤ 1
 
4.8%
Compat Jamo
ValueCountFrequency (%)
ㅇ 2
50.0%
ㅁ 1
25.0%
ㄷ 1
25.0%

교육인원
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)6.1%
Missing163
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean57.841109
Minimum1
Maximum167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.6 KiB
2023-12-13T06:35:05.508690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22
Q142
median53
Q374
95-th percentile106.8
Maximum167
Range166
Interquartile range (IQR)32

Descriptive statistics

Standard deviation25.507305
Coefficient of variation (CV)0.44098922
Kurtosis0.59622851
Mean57.841109
Median Absolute Deviation (MAD)15
Skewness0.50189616
Sum125226
Variance650.62262
MonotonicityNot monotonic
2023-12-13T06:35:05.644814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47 73
 
3.1%
50 62
 
2.7%
52 59
 
2.5%
51 53
 
2.3%
46 53
 
2.3%
45 52
 
2.2%
53 48
 
2.1%
48 47
 
2.0%
40 42
 
1.8%
54 40
 
1.7%
Other values (121) 1636
70.3%
(Missing) 163
 
7.0%
ValueCountFrequency (%)
1 9
 
0.4%
2 32
1.4%
3 8
 
0.3%
4 8
 
0.3%
5 7
 
0.3%
6 10
 
0.4%
7 2
 
0.1%
8 5
 
0.2%
9 1
 
< 0.1%
10 4
 
0.2%
ValueCountFrequency (%)
167 1
 
< 0.1%
149 1
 
< 0.1%
145 1
 
< 0.1%
142 1
 
< 0.1%
135 2
 
0.1%
133 1
 
< 0.1%
132 2
 
0.1%
131 3
0.1%
130 1
 
< 0.1%
129 5
0.2%

교육시간
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2
1630 
3
281 
6
 
148
1
 
137
4
 
38
Other values (15)
 
94

Length

Max length4
Median length1
Mean length1.0459622
Min length1

Unique

Unique7 ?
Unique (%)0.3%

Sample

1st row2
2nd row2
3rd row8
4th row4
5th row2

Common Values

ValueCountFrequency (%)
2 1630
70.0%
3 281
 
12.1%
6 148
 
6.4%
1 137
 
5.9%
4 38
 
1.6%
5 24
 
1.0%
8 22
 
0.9%
서면교육 15
 
0.6%
<NA> 15
 
0.6%
9 5
 
0.2%
Other values (10) 13
 
0.6%

Length

2023-12-13T06:35:05.799588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 1630
70.0%
3 281
 
12.1%
6 148
 
6.4%
1 137
 
5.9%
4 38
 
1.6%
5 24
 
1.0%
8 22
 
0.9%
서면교육 15
 
0.6%
na 15
 
0.6%
9 5
 
0.2%
Other values (10) 13
 
0.6%

강사
Text

Distinct71
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-13T06:35:06.014937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length5
Mean length6.1370275
Min length2

Characters and Unicode

Total characters14287
Distinct characters97
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.9%

Sample

1st row안전관리자
2nd row안전담당자
3rd row안전관리자
4th row안전관리자
5th row안전총괄자
ValueCountFrequency (%)
안전관리자 1294
40.7%
등 471
 
14.8%
관리감독자 243
 
7.6%
외부전문가 211
 
6.6%
안전담당자 125
 
3.9%
기타 106
 
3.3%
교육 83
 
2.6%
안전관리관 59
 
1.9%
비대면 56
 
1.8%
공람 56
 
1.8%
Other values (60) 479
 
15.0%
2023-12-13T06:35:06.394931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 1836
12.9%
자 1789
12.5%
관 1761
12.3%
리 1675
11.7%
안 1614
11.3%
867
 
6.1%
등 483
 
3.4%
부 296
 
2.1%
외 253
 
1.8%
감 245
 
1.7%
Other values (87) 3468
24.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13216
92.5%
Space Separator 867
 
6.1%
Other Punctuation 68
 
0.5%
Open Punctuation 57
 
0.4%
Close Punctuation 57
 
0.4%
Other Symbol 12
 
0.1%
Decimal Number 8
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 1836
13.9%
자 1789
13.5%
관 1761
13.3%
리 1675
12.7%
안 1614
12.2%
등 483
 
3.7%
부 296
 
2.2%
외 253
 
1.9%
감 245
 
1.9%
독 245
 
1.9%
Other values (77) 3019
22.8%
Other Punctuation
ValueCountFrequency (%)
, 55
80.9%
: 12
 
17.6%
. 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
867
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 12
100.0%
Decimal Number
ValueCountFrequency (%)
5 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13216
92.5%
Common 1069
 
7.5%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 1836
13.9%
자 1789
13.5%
관 1761
13.3%
리 1675
12.7%
안 1614
12.2%
등 483
 
3.7%
부 296
 
2.2%
외 253
 
1.9%
감 245
 
1.9%
독 245
 
1.9%
Other values (77) 3019
22.8%
Common
ValueCountFrequency (%)
867
81.1%
( 57
 
5.3%
) 57
 
5.3%
, 55
 
5.1%
: 12
 
1.1%
㎥ 12
 
1.1%
5 8
 
0.7%
. 1
 
0.1%
Latin
ValueCountFrequency (%)
D 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13216
92.5%
ASCII 1059
 
7.4%
CJK Compat 12
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 1836
13.9%
자 1789
13.5%
관 1761
13.3%
리 1675
12.7%
안 1614
12.2%
등 483
 
3.7%
부 296
 
2.2%
외 253
 
1.9%
감 245
 
1.9%
독 245
 
1.9%
Other values (77) 3019
22.8%
ASCII
ValueCountFrequency (%)
867
81.9%
( 57
 
5.4%
) 57
 
5.4%
, 55
 
5.2%
: 12
 
1.1%
5 8
 
0.8%
D 1
 
0.1%
H 1
 
0.1%
. 1
 
0.1%
CJK Compat
ValueCountFrequency (%)
㎥ 12
100.0%

Interactions

2023-12-13T06:35:02.613428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:35:06.488041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지 사대상교육인원교육시간강사
지 사1.0000.9900.6880.6130.885
대상0.9901.0000.8810.9290.972
교육인원0.6880.8811.0000.7410.831
교육시간0.6130.9290.7411.0000.812
강사0.8850.9720.8310.8121.000
2023-12-13T06:35:06.604716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지 사교육시간
지 사1.0000.176
교육시간0.1761.000
2023-12-13T06:35:06.694231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육인원지 사교육시간
교육인원1.0000.3390.395
지 사0.3391.0000.176
교육시간0.3950.1761.000

Missing values

2023-12-13T06:35:02.776987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:35:02.930953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

지 사일자대상교육내용교육인원교육시간강사
0중앙2014-01-06현업원2013 자체감사결과 등<NA>2안전관리자
1중앙2014-02-04현업원2014년 재난안전관리 기본계획 화학물질 MSDS 교육등<NA>2안전담당자
2중앙2014-03-03신규직원신규직원(인사이동)<NA>8안전관리자
3중앙2014-03-04작업변경자작업변경자(인사이동)<NA>4안전관리자
4중앙2014-03-04현업원지사장 교육 및 안전조작 절차<NA>2안전총괄자
5중앙2014-04-04현업원CO2 방출시 대처방안 등<NA>2안전관리자
6중앙2014-05-07현업원공정안전관리 개론<NA>2외부기관
7중앙2014-06-09현업원PSM 이행실태 점검결과 및 조치사항, 감전재해예방<NA>2안전관리자
8중앙2015-01-06중앙지사 및 협력업체 직원위험성평가 결과 교육 및 PSM 자체감사 결과 교육 등372안전관리자
9중앙2015-02-05중앙지사 및 협력업체 직원심폐소생술 교육 및 지사내 물질안전보건자료(MSDS) 교육 등372외부전문가 등
지 사일자대상교육내용교육인원교육시간강사
2318판교2022-10-04판교지사 및 협력업체직원행락철 안전가이드, 유해위험물질, 공정안전보고서 개정사항, 안전보건경영 절차서 개정사항 등542안전관리자 등
2319판교2022-11-02판교지사 및 협력업체직원다중이용시설, 기능연속성인식교육, 법규등록부 개정, 사고사례, 공정안전보고서 등542안전관리자 등
2320판교2022-12-08판교지사 및 협력업체직원심폐소생술, 고온수 누출시 행동요령, MSDS, 기능연속성경영시스템 내부심사 결과, 위험성평가 결과 등574보건관리자 등
2321판교2022-12-31판교지사 5급 이하 직원2022년 4분기 근로자 정기 안전보건교육516온라인 교육
2322판교2023-01-04판교지사 및 협력업체직원설연휴 안전사고, 응급처치 요령, PSM 자체감사 결과, KOSHA-MS 내부심사 및 경영자검토 결과 등522안전관리자 등
2323판교2023-02-03판교지사 및 협력업체직원다중이용시설, 사무실 공기질 측정, Safety Point 운영결과, 공정안전보고서 개정 등532안전관리자 등
2324판교2023-03-10판교지사 및 협력업체직원MSDS, 보호구, 해빙기 안전보건교육, 미세먼지 대응요령, 공정안전보고서 개정내용 등582보건관리자 등
2325판교2023-03-31판교지사 5급 이하 직원2023년 1분기 근로자 정기 안전보건교육516온라인 교육
2326판교2023-04-04판교지사 및 협력업체직원환절기 건강관리, 미세먼지, 호흡기 감염병 확산방지, 전기 안전교육582안전관리자 등
2327판교2023-05-09판교지사 및 협력업체직원중대재해처벌법, 밀폐공간 안전수칙, 행락철 안전사고, 작업환경측정612안전관리자 등

Duplicate rows

Most frequently occurring

지 사일자대상교육내용교육인원교육시간강사# duplicates
0분당2020-01-07우리직원, 협력업체`20년 안전보건활동 목표 및 추진계획, 우리공사 안전사고 발생 현황, 전기실 출입 안전수칙722안전관리관2
1분당2020-02-04우리직원, 협력업체분당사업소 연간 재난,산업 안전관리 계획, 우리공사 사고사례 전파, 코로나 바이러스 예방 대책 동영상 교육642안전관리관2
2분당2020-03-05우리직원해빙기 안전점검 활동 강화, 해빙기 건설현장 안전보건 길잡이, 코로나19 확산 산업안전보건분야 대응조치702안전관리관2
3분당2020-04-06우리직원질소에 의한 질식사고 사례 교육, 골다공증과 영양702안전관리자2
4분당2020-05-07우리직원, 협력업체`20년 산업안전보건법 개정사항, 분당사업소 Safety Point 운영방안, 추락재해예방 동영상 시청702안전관리자2
5분당2020-06-04우리직원, 협력업체응급처치 실무교육 및 AED 사용법562외부전문가2
6분당2022-01-03우리직원, 협력업체2022년 안전경영책임계획, 2021년 밀폐공간 작업프로그램 개정사항762안전관리자2
7분당2022-02-01분당사업소 근로자 전원계절별 건강관리, 재난안전, 직장 내 괴롭힘의 사례와 판단기준, 안전보건의 첫걸음 등476대한산업안전협회 원격교육센터2
8분당2022-02-01우리직원, 협력업체중대재해 예방을 위한 전사적 준법경영실천방안 교육, 안전보건경영시스템 관련 내용 교육772안전관리자2
9파주2022-04-06지사직원 및 협력업체4월 안전점검의 날 행사1102안전관리자 등2