Overview

Dataset statistics

Number of variables22
Number of observations377
Missing cells245
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.4 KiB
Average record size in memory180.3 B

Variable types

Numeric4
Text3
DateTime2
Categorical13

Alerts

apr_at is highly imbalanced (50.4%)Imbalance
edu_nm has 35 (9.3%) missing valuesMissing
edu_sdate has 35 (9.3%) missing valuesMissing
edu_fdate has 35 (9.3%) missing valuesMissing
edu_exp has 35 (9.3%) missing valuesMissing
period has 35 (9.3%) missing valuesMissing
lat has 35 (9.3%) missing valuesMissing
lng has 35 (9.3%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-21 12:43:44.111815
Analysis finished2024-04-21 12:43:44.848560
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct377
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5382.7215
Minimum4501
Maximum5681
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-21T21:43:45.038065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4501
5-th percentile4519.8
Q15358
median5475
Q35569
95-th percentile5662.2
Maximum5681
Range1180
Interquartile range (IQR)211

Descriptive statistics

Standard deviation320.7501
Coefficient of variation (CV)0.059588835
Kurtosis2.8651297
Mean5382.7215
Median Absolute Deviation (MAD)106
Skewness-1.9845514
Sum2029286
Variance102880.63
MonotonicityNot monotonic
2024-04-21T21:43:45.475861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5419 1
 
0.3%
5289 1
 
0.3%
5616 1
 
0.3%
5550 1
 
0.3%
5549 1
 
0.3%
5548 1
 
0.3%
5547 1
 
0.3%
5293 1
 
0.3%
5292 1
 
0.3%
5291 1
 
0.3%
Other values (367) 367
97.3%
ValueCountFrequency (%)
4501 1
0.3%
4502 1
0.3%
4503 1
0.3%
4504 1
0.3%
4505 1
0.3%
4506 1
0.3%
4507 1
0.3%
4508 1
0.3%
4509 1
0.3%
4510 1
0.3%
ValueCountFrequency (%)
5681 1
0.3%
5680 1
0.3%
5679 1
0.3%
5678 1
0.3%
5677 1
0.3%
5676 1
0.3%
5675 1
0.3%
5674 1
0.3%
5673 1
0.3%
5672 1
0.3%

instt_code
Real number (ℝ)

Distinct15
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3334695
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-21T21:43:45.843486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13320000
median3340000
Q33360000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation41049.721
Coefficient of variation (CV)0.012309888
Kurtosis-0.77221216
Mean3334695
Median Absolute Deviation (MAD)20000
Skewness-0.37069153
Sum1.25718 × 109
Variance1.6850796 × 109
MonotonicityNot monotonic
2024-04-21T21:43:46.228614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3320000 56
14.9%
3390000 45
11.9%
3380000 42
11.1%
3350000 41
10.9%
3330000 34
9.0%
3340000 30
8.0%
3360000 30
8.0%
3270000 27
7.2%
3260000 18
 
4.8%
3310000 15
 
4.0%
Other values (5) 39
10.3%
ValueCountFrequency (%)
3250000 9
 
2.4%
3260000 18
 
4.8%
3270000 27
7.2%
3280000 13
 
3.4%
3290000 3
 
0.8%
3300000 8
 
2.1%
3310000 15
 
4.0%
3320000 56
14.9%
3330000 34
9.0%
3340000 30
8.0%
ValueCountFrequency (%)
3400000 6
 
1.6%
3390000 45
11.9%
3380000 42
11.1%
3360000 30
8.0%
3350000 41
10.9%
3340000 30
8.0%
3330000 34
9.0%
3320000 56
14.9%
3310000 15
 
4.0%
3300000 8
 
2.1%

edu_nm
Text

MISSING 

Distinct192
Distinct (%)56.1%
Missing35
Missing (%)9.3%
Memory size3.1 KiB
2024-04-21T21:43:47.045984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length9.9385965
Min length2

Characters and Unicode

Total characters3399
Distinct characters202
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)36.3%

Sample

1st row스마트폰활용(기본)Ⅰ
2nd row스마트폰활용(기본)Ⅱ
3rd row[컴퓨터활용능력] 엑셀기초Ⅰ
4th row[컴퓨터활용능력] 엑셀기초Ⅱ
5th row디지털 기초
ValueCountFrequency (%)
스마트폰 35
 
5.7%
기초/활용 35
 
5.7%
활용 27
 
4.4%
기초 24
 
3.9%
인터넷 20
 
3.2%
컴퓨터 20
 
3.2%
파워포인트 19
 
3.1%
엑셀 17
 
2.8%
2010 12
 
1.9%
익히기 10
 
1.6%
Other values (192) 399
64.6%
2024-04-21T21:43:47.987790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
276
 
8.1%
기 200
 
5.9%
) 123
 
3.6%
( 123
 
3.6%
활 122
 
3.6%
용 121
 
3.6%
초 113
 
3.3%
트 107
 
3.1%
터 94
 
2.8%
스 82
 
2.4%
Other values (192) 2038
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2487
73.2%
Space Separator 276
 
8.1%
Decimal Number 223
 
6.6%
Close Punctuation 125
 
3.7%
Open Punctuation 125
 
3.7%
Uppercase Letter 71
 
2.1%
Other Punctuation 70
 
2.1%
Dash Punctuation 10
 
0.3%
Letter Number 6
 
0.2%
Lowercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 200
 
8.0%
활 122
 
4.9%
용 121
 
4.9%
초 113
 
4.5%
트 107
 
4.3%
터 94
 
3.8%
스 82
 
3.3%
인 70
 
2.8%
마 68
 
2.7%
폰 66
 
2.7%
Other values (157) 1444
58.1%
Uppercase Letter
ValueCountFrequency (%)
S 18
25.4%
T 14
19.7%
I 13
18.3%
Q 13
18.3%
N 8
11.3%
C 2
 
2.8%
W 1
 
1.4%
G 1
 
1.4%
U 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 62
27.8%
1 53
23.8%
0 45
20.2%
3 28
12.6%
4 17
 
7.6%
5 16
 
7.2%
6 2
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/ 39
55.7%
. 10
 
14.3%
& 8
 
11.4%
· 6
 
8.6%
, 5
 
7.1%
" 2
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
c 2
33.3%
h 1
16.7%
r 1
16.7%
a 1
16.7%
t 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 123
98.4%
] 2
 
1.6%
Open Punctuation
ValueCountFrequency (%)
( 123
98.4%
[ 2
 
1.6%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
50.0%
Ⅰ 3
50.0%
Space Separator
ValueCountFrequency (%)
276
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2487
73.2%
Common 829
 
24.4%
Latin 83
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 200
 
8.0%
활 122
 
4.9%
용 121
 
4.9%
초 113
 
4.5%
트 107
 
4.3%
터 94
 
3.8%
스 82
 
3.3%
인 70
 
2.8%
마 68
 
2.7%
폰 66
 
2.7%
Other values (157) 1444
58.1%
Common
ValueCountFrequency (%)
276
33.3%
) 123
14.8%
( 123
14.8%
2 62
 
7.5%
1 53
 
6.4%
0 45
 
5.4%
/ 39
 
4.7%
3 28
 
3.4%
4 17
 
2.1%
5 16
 
1.9%
Other values (9) 47
 
5.7%
Latin
ValueCountFrequency (%)
S 18
21.7%
T 14
16.9%
I 13
15.7%
Q 13
15.7%
N 8
9.6%
Ⅱ 3
 
3.6%
Ⅰ 3
 
3.6%
c 2
 
2.4%
C 2
 
2.4%
h 1
 
1.2%
Other values (6) 6
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2487
73.2%
ASCII 900
 
26.5%
None 6
 
0.2%
Number Forms 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
276
30.7%
) 123
13.7%
( 123
13.7%
2 62
 
6.9%
1 53
 
5.9%
0 45
 
5.0%
/ 39
 
4.3%
3 28
 
3.1%
S 18
 
2.0%
4 17
 
1.9%
Other values (22) 116
12.9%
Hangul
ValueCountFrequency (%)
기 200
 
8.0%
활 122
 
4.9%
용 121
 
4.9%
초 113
 
4.5%
트 107
 
4.3%
터 94
 
3.8%
스 82
 
3.3%
인 70
 
2.8%
마 68
 
2.7%
폰 66
 
2.7%
Other values (157) 1444
58.1%
None
ValueCountFrequency (%)
· 6
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
50.0%
Ⅰ 3
50.0%

edu_sdate
Date

MISSING 

Distinct59
Distinct (%)17.3%
Missing35
Missing (%)9.3%
Memory size3.1 KiB
Minimum2002-11-20 00:00:00
Maximum2023-11-20 00:00:00
2024-04-21T21:43:48.210812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:43:48.450398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

edu_fdate
Date

MISSING 

Distinct58
Distinct (%)17.0%
Missing35
Missing (%)9.3%
Memory size3.1 KiB
Minimum2004-12-20 00:00:00
Maximum2030-10-20 00:00:00
2024-04-21T21:43:48.693274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:43:48.945070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

edu_time
Categorical

Distinct25
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
10:00~12:00
107 
13:30~15:30
73 
14:00~16:00
40 
<NA>
35 
09:00~13:00
29 
Other values (20)
93 

Length

Max length11
Median length11
Mean length10.278515
Min length2

Unique

Unique8 ?
Unique (%)2.1%

Sample

1st row10:00~12:00
2nd row10:00~12:00
3rd row14:00~16:00
4th row14:00~16:00
5th row09:00~12:00

Common Values

ValueCountFrequency (%)
10:00~12:00 107
28.4%
13:30~15:30 73
19.4%
14:00~16:00 40
 
10.6%
<NA> 35
 
9.3%
09:00~13:00 29
 
7.7%
13:00~15:00 25
 
6.6%
15:30~17:30 13
 
3.4%
09:00~11:00 7
 
1.9%
11:00~13:00 7
 
1.9%
10:10~12:10 6
 
1.6%
Other values (15) 35
 
9.3%

Length

2024-04-21T21:43:49.188568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:00~12:00 107
28.4%
13:30~15:30 73
19.4%
14:00~16:00 40
 
10.6%
na 35
 
9.3%
09:00~13:00 29
 
7.7%
13:00~15:00 25
 
6.6%
15:30~17:30 13
 
3.4%
09:00~11:00 7
 
1.9%
11:00~13:00 7
 
1.9%
10:10~12:10 6
 
1.6%
Other values (15) 35
 
9.3%

edu_loc
Categorical

Distinct19
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
북구청 전산교육장
56 
사상구청 전산교육장
45 
망미동 구민정보화 교육장
42 
금정구청 4층 전산교육장
41 
<NA>
35 
Other values (14)
158 

Length

Max length18
Median length16
Mean length11.111406
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row중구청 전산교육장
2nd row중구청 전산교육장
3rd row중구청 전산교육장
4th row중구청 전산교육장
5th row중구청 전산교육장

Common Values

ValueCountFrequency (%)
북구청 전산교육장 56
14.9%
사상구청 전산교육장 45
11.9%
망미동 구민정보화 교육장 42
11.1%
금정구청 4층 전산교육장 41
10.9%
<NA> 35
9.3%
부산광역시 강서구청 30
8.0%
구민정보교육센터(동구청 5층) 27
7.2%
남구청 5층 정보화교육장 13
 
3.4%
문화복합센터 3층 정보화교육장 13
 
3.4%
영도구청 전산교육장(4층) 13
 
3.4%
Other values (9) 62
16.4%

Length

2024-04-21T21:43:49.418023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전산교육장 157
18.4%
북구청 56
 
6.5%
정보화교육장 54
 
6.3%
4층 47
 
5.5%
사상구청 45
 
5.3%
망미동 42
 
4.9%
구민정보화 42
 
4.9%
교육장 42
 
4.9%
금정구청 41
 
4.8%
5층 40
 
4.7%
Other values (23) 289
33.8%

people
Categorical

Distinct13
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
15
99 
38
42 
24
41 
20
38 
<NA>
35 
Other values (8)
122 

Length

Max length4
Median length2
Mean length2.2811671
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
15 99
26.3%
38 42
11.1%
24 41
10.9%
20 38
 
10.1%
<NA> 35
 
9.3%
30 34
 
9.0%
16명 27
 
7.2%
12 26
 
6.9%
40 16
 
4.2%
10 9
 
2.4%
Other values (3) 10
 
2.7%

Length

2024-04-21T21:43:49.656798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
15 99
26.3%
38 42
11.1%
24 41
10.9%
20 38
 
10.1%
na 35
 
9.3%
30 34
 
9.0%
16명 27
 
7.2%
12 26
 
6.9%
40 16
 
4.2%
10 9
 
2.4%
Other values (3) 10
 
2.7%

edu_exp
Text

MISSING 

Distinct117
Distinct (%)34.2%
Missing35
Missing (%)9.3%
Memory size3.1 KiB
2024-04-21T21:43:50.505797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length8
Mean length12.190058
Min length5

Characters and Unicode

Total characters4169
Distinct characters226
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

Unique83 ?
Unique (%)24.3%

Sample

1st row기본앱(문자, 카메라, 네이버지도 등) 활용
2nd row실생활 유용한 앱 활용법
3rd row엑셀 메뉴구성, 데이터입력 및 표만들기
4th row기본함수, 피벗테이블 만들기 등
5th row스마트기기 사용법, 화상솔루션
ValueCountFrequency (%)
2주과정 129
 
13.4%
초급 120
 
12.5%
중급 62
 
6.4%
1주과정 53
 
5.5%
교육취소(사유 42
 
4.4%
이용하여 15
 
1.6%
기초 14
 
1.5%
및 11
 
1.1%
과정 11
 
1.1%
동영상 11
 
1.1%
Other values (207) 494
51.4%
2024-04-21T21:43:51.581923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
626
 
15.0%
, 236
 
5.7%
정 214
 
5.1%
과 201
 
4.8%
주 191
 
4.6%
급 190
 
4.6%
초 151
 
3.6%
2 146
 
3.5%
로 79
 
1.9%
1 74
 
1.8%
Other values (216) 2061
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2790
66.9%
Space Separator 626
 
15.0%
Decimal Number 316
 
7.6%
Other Punctuation 298
 
7.1%
Close Punctuation 55
 
1.3%
Open Punctuation 55
 
1.3%
Uppercase Letter 15
 
0.4%
Lowercase Letter 14
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 214
 
7.7%
과 201
 
7.2%
주 191
 
6.8%
급 190
 
6.8%
초 151
 
5.4%
로 79
 
2.8%
중 67
 
2.4%
사 67
 
2.4%
용 60
 
2.2%
코 52
 
1.9%
Other values (176) 1518
54.4%
Lowercase Letter
ValueCountFrequency (%)
i 2
14.3%
o 2
14.3%
n 1
7.1%
d 1
7.1%
s 1
7.1%
w 1
7.1%
p 1
7.1%
r 1
7.1%
e 1
7.1%
z 1
7.1%
Other values (2) 2
14.3%
Decimal Number
ValueCountFrequency (%)
2 146
46.2%
1 74
23.4%
5 19
 
6.0%
3 19
 
6.0%
4 15
 
4.7%
0 12
 
3.8%
9 11
 
3.5%
8 11
 
3.5%
6 5
 
1.6%
7 4
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
C 3
20.0%
S 2
13.3%
Q 2
13.3%
I 2
13.3%
T 2
13.3%
W 1
 
6.7%
U 1
 
6.7%
N 1
 
6.7%
P 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 236
79.2%
: 42
 
14.1%
/ 14
 
4.7%
& 3
 
1.0%
" 2
 
0.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
626
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2790
66.9%
Common 1350
32.4%
Latin 29
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 214
 
7.7%
과 201
 
7.2%
주 191
 
6.8%
급 190
 
6.8%
초 151
 
5.4%
로 79
 
2.8%
중 67
 
2.4%
사 67
 
2.4%
용 60
 
2.2%
코 52
 
1.9%
Other values (176) 1518
54.4%
Latin
ValueCountFrequency (%)
C 3
 
10.3%
S 2
 
6.9%
i 2
 
6.9%
o 2
 
6.9%
Q 2
 
6.9%
I 2
 
6.9%
T 2
 
6.9%
W 1
 
3.4%
n 1
 
3.4%
d 1
 
3.4%
Other values (11) 11
37.9%
Common
ValueCountFrequency (%)
626
46.4%
, 236
 
17.5%
2 146
 
10.8%
1 74
 
5.5%
) 55
 
4.1%
( 55
 
4.1%
: 42
 
3.1%
5 19
 
1.4%
3 19
 
1.4%
4 15
 
1.1%
Other values (9) 63
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2790
66.9%
ASCII 1379
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
626
45.4%
, 236
 
17.1%
2 146
 
10.6%
1 74
 
5.4%
) 55
 
4.0%
( 55
 
4.0%
: 42
 
3.0%
5 19
 
1.4%
3 19
 
1.4%
4 15
 
1.1%
Other values (30) 92
 
6.7%
Hangul
ValueCountFrequency (%)
정 214
 
7.7%
과 201
 
7.2%
주 191
 
6.8%
급 190
 
6.8%
초 151
 
5.4%
로 79
 
2.8%
중 67
 
2.4%
사 67
 
2.4%
용 60
 
2.2%
코 52
 
1.9%
Other values (176) 1518
54.4%

road_addr
Categorical

Distinct18
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
부산광역시 북구 낙동대로1570번길 33(구포동)
56 
부산광역시 사상구 학감대로 242
45 
부산광역시 수영구 연수로 275번길 30
42 
부산 금정구 중앙대로 1777
41 
<NA>
35 
Other values (13)
158 

Length

Max length27
Median length21
Mean length19.148541
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row부산광역시 중구로120(지하1층 전산교육장)
2nd row부산광역시 중구로120(지하1층 전산교육장)
3rd row부산광역시 중구로120(지하1층 전산교육장)
4th row부산광역시 중구로120(지하1층 전산교육장)
5th row부산광역시 중구로120(지하1층 전산교육장)

Common Values

ValueCountFrequency (%)
부산광역시 북구 낙동대로1570번길 33(구포동) 56
14.9%
부산광역시 사상구 학감대로 242 45
11.9%
부산광역시 수영구 연수로 275번길 30 42
11.1%
부산 금정구 중앙대로 1777 41
10.9%
<NA> 35
9.3%
부산광역시 강서구 낙동북로 477(대저1동) 30
8.0%
부산광역시 동구 구청로 1(수정동) 27
7.2%
부산광역시 서구 구덕로 120 18
 
4.8%
부산 해운대구 재반로211번길 9 13
 
3.4%
부산광역시 남구 못골로 19 13
 
3.4%
Other values (8) 57
15.1%

Length

2024-04-21T21:43:51.801098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 276
 
19.0%
부산 66
 
4.5%
북구 56
 
3.8%
낙동대로1570번길 56
 
3.8%
33(구포동 56
 
3.8%
사상구 45
 
3.1%
학감대로 45
 
3.1%
242 45
 
3.1%
30 45
 
3.1%
수영구 42
 
2.9%
Other values (43) 723
49.7%

addr
Categorical

Distinct14
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
93 
부산광역시 북구 구포동 1124-1 북구청
56 
부산광역시 사상구 감전동 138-8
45 
부산광역시 수영구 망미동 826-54, 2층
42 
부산 금정구 부곡3동 78
41 
Other values (9)
100 

Length

Max length25
Median length23
Mean length16.297082
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row부산광역시 중구 120호
2nd row부산광역시 중구 120호
3rd row부산광역시 중구 120호
4th row부산광역시 중구 120호
5th row부산광역시 중구 120호

Common Values

ValueCountFrequency (%)
<NA> 93
24.7%
부산광역시 북구 구포동 1124-1 북구청 56
14.9%
부산광역시 사상구 감전동 138-8 45
11.9%
부산광역시 수영구 망미동 826-54, 2층 42
11.1%
부산 금정구 부곡3동 78 41
10.9%
부산광역시 강서구 대저1동 2300 강서구청 30
 
8.0%
부산광역시 서구 토성동4가 2-3 18
 
4.8%
부산광역시 남구 대연동 1268-1 13
 
3.4%
부산광역시 영도구 청학동 48-3번지 13
 
3.4%
부산광역시 중구 120호 9
 
2.4%
Other values (4) 17
 
4.5%

Length

2024-04-21T21:43:52.215550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 243
 
17.9%
na 93
 
6.9%
북구 56
 
4.1%
구포동 56
 
4.1%
1124-1 56
 
4.1%
북구청 56
 
4.1%
사상구 45
 
3.3%
감전동 45
 
3.3%
138-8 45
 
3.3%
2층 42
 
3.1%
Other values (35) 619
45.6%

months
Categorical

Distinct34
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
85 
9
34 
10
23 
11
22 
8
20 
Other values (29)
193 

Length

Max length4
Median length3
Mean length2.198939
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row9

Common Values

ValueCountFrequency (%)
<NA> 85
22.5%
9 34
 
9.0%
10 23
 
6.1%
11 22
 
5.8%
8 20
 
5.3%
7 16
 
4.2%
1 15
 
4.0%
6월 13
 
3.4%
7월 12
 
3.2%
6 10
 
2.7%
Other values (24) 127
33.7%

Length

2024-04-21T21:43:52.431536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 85
22.5%
9 34
 
9.0%
10 23
 
6.1%
11 22
 
5.8%
8 20
 
5.3%
7 16
 
4.2%
1 15
 
4.0%
6월 13
 
3.4%
7월 12
 
3.2%
6 10
 
2.7%
Other values (24) 127
33.7%

target
Categorical

Distinct23
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
구민
96 
주민등록상 금정구민
41 
<NA>
35 
강서구 주민
30 
동구 주민
27 
Other values (18)
148 

Length

Max length15
Median length11
Mean length5.1485411
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row지역 주민
2nd row지역 주민
3rd row지역 주민
4th row지역 주민
5th row지역 주민

Common Values

ValueCountFrequency (%)
구민 96
25.5%
주민등록상 금정구민 41
10.9%
<NA> 35
 
9.3%
강서구 주민 30
 
8.0%
동구 주민 27
 
7.2%
55세 이상 22
 
5.8%
55세 미만 19
 
5.0%
해운대구민 17
 
4.5%
영도구민 누구나 12
 
3.2%
디지털 취약계층 12
 
3.2%
Other values (13) 66
17.5%

Length

2024-04-21T21:43:52.662010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구민 96
16.9%
주민 66
11.6%
금정구민 41
 
7.2%
55세 41
 
7.2%
주민등록상 41
 
7.2%
na 35
 
6.2%
강서구 30
 
5.3%
동구 27
 
4.8%
이상 22
 
3.9%
미만 19
 
3.3%
Other values (21) 150
26.4%

period
Text

MISSING 

Distinct70
Distinct (%)20.5%
Missing35
Missing (%)9.3%
Memory size3.1 KiB
2024-04-21T21:43:53.352782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length16
Mean length13.435673
Min length2

Characters and Unicode

Total characters4595
Distinct characters45
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)2.0%

Sample

1st row2020-08-05
2nd row2020-08-05
3rd row2020-08-05
4th row2020-08-05
5th row2020-08-05
ValueCountFrequency (%)
9/1(화)~마감시까지 15
 
4.0%
7/1(수)~마감시까지 15
 
4.0%
6/1(월)~마감시까지 14
 
3.7%
10/5(월)~마감시까지 13
 
3.5%
1/2(목)~마감시까지 12
 
3.2%
항시 12
 
3.2%
8/3(월)~마감시까지 12
 
3.2%
3/2(월)~마감시까지 10
 
2.7%
10/21~마감시까지 9
 
2.4%
2020-08-05 9
 
2.4%
Other values (67) 254
67.7%
2024-04-21T21:43:54.254935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 525
 
11.4%
2 433
 
9.4%
1 410
 
8.9%
~ 297
 
6.5%
- 280
 
6.1%
시 252
 
5.5%
/ 247
 
5.4%
까 237
 
5.2%
지 237
 
5.2%
마 231
 
5.0%
Other values (35) 1446
31.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1790
39.0%
Other Letter 1520
33.1%
Math Symbol 297
 
6.5%
Dash Punctuation 280
 
6.1%
Other Punctuation 257
 
5.6%
Open Punctuation 209
 
4.5%
Close Punctuation 209
 
4.5%
Space Separator 33
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 252
16.6%
까 237
15.6%
지 237
15.6%
마 231
15.2%
감 231
15.2%
월 106
7.0%
수 47
 
3.1%
부 27
 
1.8%
터 27
 
1.8%
목 20
 
1.3%
Other values (18) 105
6.9%
Decimal Number
ValueCountFrequency (%)
0 525
29.3%
2 433
24.2%
1 410
22.9%
5 90
 
5.0%
3 84
 
4.7%
9 63
 
3.5%
8 59
 
3.3%
6 48
 
2.7%
7 48
 
2.7%
4 30
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 247
96.1%
. 10
 
3.9%
Math Symbol
ValueCountFrequency (%)
~ 297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 280
100.0%
Open Punctuation
ValueCountFrequency (%)
( 209
100.0%
Close Punctuation
ValueCountFrequency (%)
) 209
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3075
66.9%
Hangul 1520
33.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 252
16.6%
까 237
15.6%
지 237
15.6%
마 231
15.2%
감 231
15.2%
월 106
7.0%
수 47
 
3.1%
부 27
 
1.8%
터 27
 
1.8%
목 20
 
1.3%
Other values (18) 105
6.9%
Common
ValueCountFrequency (%)
0 525
17.1%
2 433
14.1%
1 410
13.3%
~ 297
9.7%
- 280
9.1%
/ 247
8.0%
( 209
 
6.8%
) 209
 
6.8%
5 90
 
2.9%
3 84
 
2.7%
Other values (7) 291
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3075
66.9%
Hangul 1520
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 525
17.1%
2 433
14.1%
1 410
13.3%
~ 297
9.7%
- 280
9.1%
/ 247
8.0%
( 209
 
6.8%
) 209
 
6.8%
5 90
 
2.9%
3 84
 
2.7%
Other values (7) 291
9.5%
Hangul
ValueCountFrequency (%)
시 252
16.6%
까 237
15.6%
지 237
15.6%
마 231
15.2%
감 231
15.2%
월 106
7.0%
수 47
 
3.1%
부 27
 
1.8%
터 27
 
1.8%
목 20
 
1.3%
Other values (18) 105
6.9%

tel
Categorical

Distinct17
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
051-309-4301
56 
051-310-4301
45 
051-610-4301
42 
051-519-4301
41 
<NA>
35 
Other values (12)
158 

Length

Max length12
Median length12
Mean length11.090186
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1588-2670
2nd row1588-2670
3rd row1588-2670
4th row1588-2670
5th row1588-2670

Common Values

ValueCountFrequency (%)
051-309-4301 56
14.9%
051-310-4301 45
11.9%
051-610-4301 42
11.1%
051-519-4301 41
10.9%
<NA> 35
9.3%
051-970-4301 30
8.0%
051-440-4301 27
7.2%
051-749-4306 25
6.6%
051-607-4301 13
 
3.4%
051-419-4301 13
 
3.4%
Other values (7) 50
13.3%

Length

2024-04-21T21:43:54.499891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-309-4301 56
14.9%
051-310-4301 45
11.9%
051-610-4301 42
11.1%
051-519-4301 41
10.9%
na 35
9.3%
051-970-4301 30
8.0%
051-440-4301 27
7.2%
051-749-4306 25
6.6%
051-419-4301 13
 
3.4%
051-607-4301 13
 
3.4%
Other values (7) 50
13.3%

days
Categorical

Distinct14
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
10
127 
<NA>
85 
5
71 
4
29 
10일
22 
Other values (9)
43 

Length

Max length4
Median length3
Mean length2.2175066
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
10 127
33.7%
<NA> 85
22.5%
5 71
18.8%
4 29
 
7.7%
10일 22
 
5.8%
9 15
 
4.0%
5일 11
 
2.9%
15일 5
 
1.3%
15 3
 
0.8%
12 2
 
0.5%
Other values (4) 7
 
1.9%

Length

2024-04-21T21:43:54.736430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10 127
33.7%
na 85
22.5%
5 71
18.8%
4 29
 
7.7%
10일 22
 
5.8%
9 15
 
4.0%
5일 11
 
2.9%
15일 5
 
1.3%
15 3
 
0.8%
12 2
 
0.5%
Other values (4) 7
 
1.9%

gugun
Categorical

Distinct16
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
부산광역시 북구
56 
부산광역시 사상구
45 
부산광역시 수영구
42 
부산광역시 금정구
41 
<NA>
35 
Other values (11)
158 

Length

Max length10
Median length9
Mean length8.2838196
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 중구
2nd row부산광역시 중구
3rd row부산광역시 중구
4th row부산광역시 중구
5th row부산광역시 중구

Common Values

ValueCountFrequency (%)
부산광역시 북구 56
14.9%
부산광역시 사상구 45
11.9%
부산광역시 수영구 42
11.1%
부산광역시 금정구 41
10.9%
<NA> 35
9.3%
부산광역시 강서구 30
8.0%
부산광역시 동구 27
7.2%
부산광역시 해운대구 25
6.6%
부산광역시 서구 18
 
4.8%
부산광역시 남구 13
 
3.4%
Other values (6) 45
11.9%

Length

2024-04-21T21:43:54.957356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 342
47.6%
북구 56
 
7.8%
사상구 45
 
6.3%
수영구 42
 
5.8%
금정구 41
 
5.7%
na 35
 
4.9%
강서구 30
 
4.2%
동구 27
 
3.8%
해운대구 25
 
3.5%
서구 18
 
2.5%
Other values (7) 58
 
8.1%

data_day
Categorical

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2020-07-31
240 
2020-08-31
42 
<NA>
35 
2020-08-20
27 
2020-09-01
25 

Length

Max length10
Median length10
Mean length9.4429708
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-07-31
2nd row2020-07-31
3rd row2020-07-31
4th row2020-07-31
5th row2020-07-31

Common Values

ValueCountFrequency (%)
2020-07-31 240
63.7%
2020-08-31 42
 
11.1%
<NA> 35
 
9.3%
2020-08-20 27
 
7.2%
2020-09-01 25
 
6.6%
2020-08-25 8
 
2.1%

Length

2024-04-21T21:43:55.179415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:43:55.382629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-07-31 240
63.7%
2020-08-31 42
 
11.1%
na 35
 
9.3%
2020-08-20 27
 
7.2%
2020-09-01 25
 
6.6%
2020-08-25 8
 
2.1%

lat
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)5.0%
Missing35
Missing (%)9.3%
Infinite0
Infinite (%)0.0%
Mean35.165313
Minimum35.091214
Maximum35.243477
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-21T21:43:55.577747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.091214
5-th percentile35.097539
Q135.129297
median35.170886
Q335.19688
95-th percentile35.243073
Maximum35.243477
Range0.152263
Interquartile range (IQR)0.067582343

Descriptive statistics

Standard deviation0.044674397
Coefficient of variation (CV)0.0012704109
Kurtosis-0.81035972
Mean35.165313
Median Absolute Deviation (MAD)0.025993736
Skewness0.18425812
Sum12026.537
Variance0.0019958017
MonotonicityNot monotonic
2024-04-21T21:43:55.784767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
35.1968797 56
14.9%
35.152612 45
11.9%
35.174512 42
11.1%
35.243073 41
10.9%
35.121299 30
8.0%
35.1292973572 27
7.2%
35.0975385517 18
 
4.8%
35.091214 13
 
3.4%
35.136501 13
 
3.4%
35.1823183 13
 
3.4%
Other values (7) 44
11.7%
(Missing) 35
9.3%
ValueCountFrequency (%)
35.091214 13
 
3.4%
35.0975385517 18
 
4.8%
35.1020144 9
 
2.4%
35.104502 6
 
1.6%
35.121299 30
8.0%
35.1292973572 27
7.2%
35.136501 13
 
3.4%
35.152612 45
11.9%
35.1628329417 3
 
0.8%
35.1708859643 12
 
3.2%
ValueCountFrequency (%)
35.243477 6
 
1.6%
35.243073 41
10.9%
35.211951 1
 
0.3%
35.1968797 56
14.9%
35.196527 7
 
1.9%
35.1823183 13
 
3.4%
35.174512 42
11.1%
35.1708859643 12
 
3.2%
35.1628329417 3
 
0.8%
35.152612 45
11.9%

lng
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)5.0%
Missing35
Missing (%)9.3%
Infinite0
Infinite (%)0.0%
Mean129.04713
Minimum128.97479
Maximum129.22295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-21T21:43:56.059131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.97479
5-th percentile128.98059
Q1128.99009
median129.04529
Q3129.09213
95-th percentile129.17146
Maximum129.22295
Range0.248163
Interquartile range (IQR)0.1020425

Descriptive statistics

Standard deviation0.059128637
Coefficient of variation (CV)0.00045819412
Kurtosis-0.19582333
Mean129.04713
Median Absolute Deviation (MAD)0.054137029
Skewness0.63217835
Sum44134.119
Variance0.0034961958
MonotonicityNot monotonic
2024-04-21T21:43:56.419585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
128.9900905 56
14.9%
128.991157 45
11.9%
129.10107 42
11.1%
129.092133 41
10.9%
128.980589 30
8.0%
129.045294029 27
7.2%
129.0234239983 18
 
4.8%
129.067914 13
 
3.4%
129.08411 13
 
3.4%
129.1192727 13
 
3.4%
Other values (7) 44
11.7%
(Missing) 35
9.3%
ValueCountFrequency (%)
128.974788 6
 
1.6%
128.980589 30
8.0%
128.9900905 56
14.9%
128.991157 45
11.9%
129.0234239983 18
 
4.8%
129.0313443 9
 
2.4%
129.045294029 27
7.2%
129.0531875593 3
 
0.8%
129.067914 13
 
3.4%
129.08411 13
 
3.4%
ValueCountFrequency (%)
129.222951 6
 
1.6%
129.1742090045 12
 
3.2%
129.1192727 13
 
3.4%
129.10107 42
11.1%
129.093097 7
 
1.9%
129.092133 41
10.9%
129.090549 1
 
0.3%
129.08411 13
 
3.4%
129.067914 13
 
3.4%
129.0531875593 3
 
0.8%

apr_at
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
336 
41 

Length

Max length4
Median length4
Mean length3.6737401
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 336
89.1%
41
 
10.9%

Length

2024-04-21T21:43:56.825924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:43:57.156277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 336
100.0%

last_load_dttm
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2020-12-21 15:06:46
321 
2020-12-21 15:06:45
56 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-21 15:06:45
2nd row2020-12-21 15:06:45
3rd row2020-12-21 15:06:45
4th row2020-12-21 15:06:45
5th row2020-12-21 15:06:45

Common Values

ValueCountFrequency (%)
2020-12-21 15:06:46 321
85.1%
2020-12-21 15:06:45 56
 
14.9%

Length

2024-04-21T21:43:57.495704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:43:57.811329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-21 377
50.0%
15:06:46 321
42.6%
15:06:45 56
 
7.4%

Sample

skeyinstt_codeedu_nmedu_sdateedu_fdateedu_timeedu_locpeopleedu_exproad_addraddrmonthstargetperiodteldaysgugundata_daylatlngapr_atlast_load_dttm
054193250000스마트폰활용(기본)Ⅰ2020-09-032020-09-1110:00~12:00중구청 전산교육장10기본앱(문자, 카메라, 네이버지도 등) 활용부산광역시 중구로120(지하1층 전산교육장)부산광역시 중구 120호9지역 주민2020-08-051588-26704부산광역시 중구2020-07-3135.102014129.031344<NA>2020-12-21 15:06:45
154203250000스마트폰활용(기본)Ⅱ2020-09-172020-09-2510:00~12:00중구청 전산교육장10실생활 유용한 앱 활용법부산광역시 중구로120(지하1층 전산교육장)부산광역시 중구 120호9지역 주민2020-08-051588-26704부산광역시 중구2020-07-3135.102014129.031344<NA>2020-12-21 15:06:45
254213250000[컴퓨터활용능력] 엑셀기초Ⅰ2020-09-072020-09-1514:00~16:00중구청 전산교육장10엑셀 메뉴구성, 데이터입력 및 표만들기부산광역시 중구로120(지하1층 전산교육장)부산광역시 중구 120호9지역 주민2020-08-051588-26704부산광역시 중구2020-07-3135.102014129.031344<NA>2020-12-21 15:06:45
354223250000[컴퓨터활용능력] 엑셀기초Ⅱ2020-09-252020-09-2914:00~16:00중구청 전산교육장10기본함수, 피벗테이블 만들기 등부산광역시 중구로120(지하1층 전산교육장)부산광역시 중구 120호9지역 주민2020-08-051588-26704부산광역시 중구2020-07-3135.102014129.031344<NA>2020-12-21 15:06:45
454233250000디지털 기초2020-09-142020-09-2509:00~12:00중구청 전산교육장10스마트기기 사용법, 화상솔루션부산광역시 중구로120(지하1층 전산교육장)부산광역시 중구 120호9지역 주민2020-08-051588-26704부산광역시 중구2020-07-3135.102014129.031344<NA>2020-12-21 15:06:45
554243250000디지털 생활2020-09-072020-09-2509:00~12:00중구청 전산교육장10교통, 금웅 등 일상생활에서 자주 이용하는 디지털 서비스 학습부산광역시 중구로120(지하1층 전산교육장)부산광역시 중구 120호9지역 주민2020-08-051588-26704부산광역시 중구2020-07-3135.102014129.031344<NA>2020-12-21 15:06:45
654823390000스마트폰 기초/활용2020-05-042020-05-1510:00~12:00사상구청 전산교육장20초급, 2주과정부산광역시 사상구 학감대로 242부산광역시 사상구 감전동 138-8555세 이상4/15(수)~마감시까지051-310-43019부산광역시 사상구2020-07-3135.152612128.991157<NA>2020-12-21 15:06:45
754833390000파워포인트 기초/활용2020-05-042020-05-1513:30~15:30사상구청 전산교육장30중급, 2주과정부산광역시 사상구 학감대로 242부산광역시 사상구 감전동 138-8555세 미만4/15(수)~마감시까지051-310-43019부산광역시 사상구2020-07-3135.152612128.991157<NA>2020-12-21 15:06:45
854843390000컴퓨터 기초/활용2020-05-182020-05-2910:00~12:00사상구청 전산교육장30초급, 2주과정부산광역시 사상구 학감대로 242부산광역시 사상구 감전동 138-8555세 이상4/15(수)~마감시까지051-310-430110부산광역시 사상구2020-07-3135.152612128.991157<NA>2020-12-21 15:06:45
954853390000사진 편집2020-05-182020-05-2913:30~15:30사상구청 전산교육장30중급, 2주과정부산광역시 사상구 학감대로 242부산광역시 사상구 감전동 138-8555세 미만4/15(수)~마감시까지051-310-430110부산광역시 사상구2020-07-3135.152612128.991157<NA>2020-12-21 15:06:45
skeyinstt_codeedu_nmedu_sdateedu_fdateedu_timeedu_locpeopleedu_exproad_addraddrmonthstargetperiodteldaysgugundata_daylatlngapr_atlast_load_dttm
36755373330000스마트폰 활용20. 11. 2320. 12. 413:30~15:30문화복합센터 3층 정보화교육장12중급, 2주과정부산 해운대구 재반로211번길 9<NA>11해운대구민10/21~마감시까지051-749-430610부산광역시 해운대구2020-09-0135.182318129.119273<NA>2020-12-21 15:06:46
36855383330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
36955393330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
37055403330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
37155413330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
37255423330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
37355433330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
37455443330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
37555453330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46
37655463330000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-12-21 15:06:46