Overview

Dataset statistics

Number of variables16
Number of observations998
Missing cells1197
Missing cells (%)7.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory131.7 KiB
Average record size in memory135.1 B

Variable types

Numeric6
Text5
Categorical5

Dataset

Description일정 아이디,일정 제목,날짜 처음,날짜 마지막,시간 처음,시간 마지막,일정 타입,일정구분,주기,주기명,주기 값,후원자,장소,시,참고 URL,일정 콘텐츠
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15478/S/1/datasetView.do

Alerts

주기 is highly overall correlated with 주기명 and 1 other fieldsHigh correlation
주기 값 is highly overall correlated with 날짜 마지막 and 2 other fieldsHigh correlation
주기명 is highly overall correlated with 주기 and 1 other fieldsHigh correlation
일정 아이디 is highly overall correlated with 날짜 처음 and 1 other fieldsHigh correlation
날짜 처음 is highly overall correlated with 일정 아이디 and 1 other fieldsHigh correlation
날짜 마지막 is highly overall correlated with 일정 아이디 and 2 other fieldsHigh correlation
일정 타입 is highly overall correlated with 일정구분High correlation
일정구분 is highly overall correlated with 일정 타입High correlation
주기 is highly imbalanced (77.8%)Imbalance
주기명 is highly imbalanced (77.8%)Imbalance
주기 값 is highly imbalanced (81.7%)Imbalance
시 is highly imbalanced (59.4%)Imbalance
후원자 has 214 (21.4%) missing valuesMissing
장소 has 162 (16.2%) missing valuesMissing
참고 URL has 784 (78.6%) missing valuesMissing
일정 콘텐츠 has 37 (3.7%) missing valuesMissing
날짜 마지막 is highly skewed (γ1 = -31.49646479)Skewed
일정 아이디 has unique valuesUnique
시간 처음 has 128 (12.8%) zerosZeros
시간 마지막 has 132 (13.2%) zerosZeros

Reproduction

Analysis started2024-05-11 08:38:10.156520
Analysis finished2024-05-11 08:38:34.544188
Duration24.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일정 아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct998
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3359.4669
Minimum202
Maximum7527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T08:38:34.865443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202
5-th percentile598
Q11771.25
median3256
Q34522.75
95-th percentile7293.9
Maximum7527
Range7325
Interquartile range (IQR)2751.5

Descriptive statistics

Standard deviation1891.9874
Coefficient of variation (CV)0.56318082
Kurtosis-0.61196968
Mean3359.4669
Median Absolute Deviation (MAD)1390.5
Skewness0.3379078
Sum3352748
Variance3579616.1
MonotonicityNot monotonic
2024-05-11T08:38:35.417435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7442 1
 
0.1%
2406 1
 
0.1%
2486 1
 
0.1%
2448 1
 
0.1%
2447 1
 
0.1%
2467 1
 
0.1%
2429 1
 
0.1%
2466 1
 
0.1%
2386 1
 
0.1%
2446 1
 
0.1%
Other values (988) 988
99.0%
ValueCountFrequency (%)
202 1
0.1%
221 1
0.1%
222 1
0.1%
223 1
0.1%
241 1
0.1%
242 1
0.1%
243 1
0.1%
244 1
0.1%
245 1
0.1%
246 1
0.1%
ValueCountFrequency (%)
7527 1
0.1%
7514 1
0.1%
7513 1
0.1%
7512 1
0.1%
7510 1
0.1%
7509 1
0.1%
7491 1
0.1%
7490 1
0.1%
7488 1
0.1%
7487 1
0.1%

일정 제목
Text

Distinct592
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2024-05-11T08:38:36.087974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length42
Mean length18.522044
Min length4

Characters and Unicode

Total characters18485
Distinct characters555
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique477 ?
Unique (%)47.8%

Sample

1st row책읽는 서울광장
2nd row책읽는 맑은냇가
3rd row책읽는 서울광장
4th row책읽는 서울광장
5th row광화문 야외마당
ValueCountFrequency (%)
98
 
2.4%
전시 70
 
1.7%
展 66
 
1.6%
강연 63
 
1.5%
책읽는 55
 
1.3%
도서전시 54
 
1.3%
서울도서관 41
 
1.0%
날 38
 
0.9%
기획전시 38
 
0.9%
서울광장 36
 
0.9%
Other values (1293) 3565
86.4%
2024-05-11T08:38:37.398520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3214
 
17.4%
서 635
 
3.4%
시 468
 
2.5%
도 373
 
2.0%
전 371
 
2.0%
] 315
 
1.7%
[ 314
 
1.7%
책 308
 
1.7%
강 280
 
1.5%
의 267
 
1.4%
Other values (545) 11940
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11993
64.9%
Space Separator 3214
 
17.4%
Lowercase Letter 691
 
3.7%
Decimal Number 671
 
3.6%
Other Punctuation 499
 
2.7%
Close Punctuation 484
 
2.6%
Open Punctuation 484
 
2.6%
Uppercase Letter 338
 
1.8%
Dash Punctuation 55
 
0.3%
Math Symbol 49
 
0.3%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 635
 
5.3%
시 468
 
3.9%
도 373
 
3.1%
전 371
 
3.1%
책 308
 
2.6%
강 280
 
2.3%
의 267
 
2.2%
기 249
 
2.1%
울 213
 
1.8%
는 209
 
1.7%
Other values (458) 8620
71.9%
Lowercase Letter
ValueCountFrequency (%)
r 80
11.6%
o 79
11.4%
e 75
10.9%
n 67
9.7%
a 62
9.0%
i 56
 
8.1%
s 42
 
6.1%
l 31
 
4.5%
t 30
 
4.3%
k 25
 
3.6%
Other values (15) 144
20.8%
Uppercase Letter
ValueCountFrequency (%)
T 41
12.1%
B 37
 
10.9%
E 33
 
9.8%
N 21
 
6.2%
A 21
 
6.2%
V 20
 
5.9%
G 19
 
5.6%
S 18
 
5.3%
O 17
 
5.0%
M 16
 
4.7%
Other values (12) 95
28.1%
Other Punctuation
ValueCountFrequency (%)
' 209
41.9%
, 124
24.8%
: 66
 
13.2%
! 42
 
8.4%
? 39
 
7.8%
& 10
 
2.0%
. 5
 
1.0%
; 2
 
0.4%
@ 1
 
0.2%
# 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 177
26.4%
2 129
19.2%
0 125
18.6%
6 68
 
10.1%
4 50
 
7.5%
5 49
 
7.3%
3 34
 
5.1%
9 21
 
3.1%
7 11
 
1.6%
8 7
 
1.0%
Close Punctuation
ValueCountFrequency (%)
] 315
65.1%
) 106
 
21.9%
」 55
 
11.4%
』 6
 
1.2%
》 2
 
0.4%
Open Punctuation
ValueCountFrequency (%)
[ 314
64.9%
( 107
 
22.1%
「 55
 
11.4%
『 6
 
1.2%
《 2
 
0.4%
Math Symbol
ValueCountFrequency (%)
> 25
51.0%
< 23
46.9%
~ 1
 
2.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
66.7%
” 1
33.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
66.7%
“ 1
33.3%
Space Separator
ValueCountFrequency (%)
3214
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11847
64.1%
Common 5463
29.6%
Latin 1029
 
5.6%
Han 146
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 635
 
5.4%
시 468
 
4.0%
도 373
 
3.1%
전 371
 
3.1%
책 308
 
2.6%
강 280
 
2.4%
의 267
 
2.3%
기 249
 
2.1%
울 213
 
1.8%
는 209
 
1.8%
Other values (452) 8474
71.5%
Latin
ValueCountFrequency (%)
r 80
 
7.8%
o 79
 
7.7%
e 75
 
7.3%
n 67
 
6.5%
a 62
 
6.0%
i 56
 
5.4%
s 42
 
4.1%
T 41
 
4.0%
B 37
 
3.6%
E 33
 
3.2%
Other values (37) 457
44.4%
Common
ValueCountFrequency (%)
3214
58.8%
] 315
 
5.8%
[ 314
 
5.7%
' 209
 
3.8%
1 177
 
3.2%
2 129
 
2.4%
0 125
 
2.3%
, 124
 
2.3%
( 107
 
2.0%
) 106
 
1.9%
Other values (30) 643
 
11.8%
Han
ValueCountFrequency (%)
展 132
90.4%
自 4
 
2.7%
聽 4
 
2.7%
休 4
 
2.7%
神 1
 
0.7%
讀 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11847
64.1%
ASCII 6360
34.4%
CJK 146
 
0.8%
None 126
 
0.7%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3214
50.5%
] 315
 
5.0%
[ 314
 
4.9%
' 209
 
3.3%
1 177
 
2.8%
2 129
 
2.0%
0 125
 
2.0%
, 124
 
1.9%
( 107
 
1.7%
) 106
 
1.7%
Other values (67) 1540
24.2%
Hangul
ValueCountFrequency (%)
서 635
 
5.4%
시 468
 
4.0%
도 373
 
3.1%
전 371
 
3.1%
책 308
 
2.6%
강 280
 
2.4%
의 267
 
2.3%
기 249
 
2.1%
울 213
 
1.8%
는 209
 
1.8%
Other values (452) 8474
71.5%
CJK
ValueCountFrequency (%)
展 132
90.4%
自 4
 
2.7%
聽 4
 
2.7%
休 4
 
2.7%
神 1
 
0.7%
讀 1
 
0.7%
None
ValueCountFrequency (%)
「 55
43.7%
」 55
43.7%
『 6
 
4.8%
』 6
 
4.8%
》 2
 
1.6%
《 2
 
1.6%
Punctuation
ValueCountFrequency (%)
’ 2
33.3%
‘ 2
33.3%
” 1
16.7%
“ 1
16.7%

날짜 처음
Real number (ℝ)

HIGH CORRELATION 

Distinct666
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20163091
Minimum20120917
Maximum20240531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T08:38:37.902889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120917
5-th percentile20130493
Q120141210
median20160820
Q320170523
95-th percentile20240413
Maximum20240531
Range119614
Interquartile range (IQR)29313.5

Descriptive statistics

Standard deviation25667.894
Coefficient of variation (CV)0.0012730138
Kurtosis2.5393729
Mean20163091
Median Absolute Deviation (MAD)10016.5
Skewness1.420072
Sum2.0122765 × 1010
Variance6.5884076 × 108
MonotonicityDecreasing
2024-05-11T08:38:38.398360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170704 8
 
0.8%
20170516 7
 
0.7%
20170801 7
 
0.7%
20170502 6
 
0.6%
20170523 6
 
0.6%
20160802 5
 
0.5%
20170510 5
 
0.5%
20170530 5
 
0.5%
20160507 5
 
0.5%
20170221 5
 
0.5%
Other values (656) 939
94.1%
ValueCountFrequency (%)
20120917 1
0.1%
20120924 1
0.1%
20121013 1
0.1%
20121026 2
0.2%
20121109 1
0.1%
20121110 1
0.1%
20121114 1
0.1%
20121115 1
0.1%
20121116 1
0.1%
20121121 1
0.1%
ValueCountFrequency (%)
20240531 2
0.2%
20240530 1
 
0.1%
20240526 2
0.2%
20240525 3
0.3%
20240524 4
0.4%
20240523 1
 
0.1%
20240519 2
0.2%
20240518 3
0.3%
20240517 3
0.3%
20240516 2
0.2%

날짜 마지막
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct684
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20144933
Minimum2017030
Maximum20240531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T08:38:38.893003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017030
5-th percentile20130493
Q120141210
median20160821
Q320170528
95-th percentile20240419
Maximum20240531
Range18223501
Interquartile range (IQR)29318.5

Descriptive statistics

Standard deviation574977.31
Coefficient of variation (CV)0.028542032
Kurtosis994.01558
Mean20144933
Median Absolute Deviation (MAD)10082
Skewness-31.496465
Sum2.0104643 × 1010
Variance3.305989 × 1011
MonotonicityNot monotonic
2024-05-11T08:38:39.316688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170730 8
 
0.8%
20170903 7
 
0.7%
20170502 6
 
0.6%
20170528 6
 
0.6%
20150925 5
 
0.5%
20170514 5
 
0.5%
20170228 5
 
0.5%
20170226 5
 
0.5%
20170219 5
 
0.5%
20170212 5
 
0.5%
Other values (674) 941
94.3%
ValueCountFrequency (%)
2017030 1
0.1%
20120921 1
0.1%
20120925 1
0.1%
20121013 1
0.1%
20121026 1
0.1%
20121028 1
0.1%
20121109 1
0.1%
20121110 1
0.1%
20121114 1
0.1%
20121115 1
0.1%
ValueCountFrequency (%)
20240531 3
0.3%
20240530 1
 
0.1%
20240526 2
0.2%
20240525 3
0.3%
20240524 4
0.4%
20240523 1
 
0.1%
20240519 2
0.2%
20240518 3
0.3%
20240517 3
0.3%
20240516 2
0.2%

시간 처음
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1059.2084
Minimum0
Maximum2000
Zeros128
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T08:38:39.867977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1900
median900
Q31400
95-th percentile1900
Maximum2000
Range2000
Interquartile range (IQR)500

Descriptive statistics

Standard deviation548.0139
Coefficient of variation (CV)0.51738061
Kurtosis-0.20056004
Mean1059.2084
Median Absolute Deviation (MAD)130
Skewness-0.25824616
Sum1057090
Variance300319.23
MonotonicityNot monotonic
2024-05-11T08:38:40.556940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
900 385
38.6%
1900 136
 
13.6%
0 128
 
12.8%
1000 96
 
9.6%
1400 71
 
7.1%
1600 32
 
3.2%
1100 24
 
2.4%
1200 24
 
2.4%
1500 23
 
2.3%
2000 11
 
1.1%
Other values (17) 68
 
6.8%
ValueCountFrequency (%)
0 128
 
12.8%
700 1
 
0.1%
800 7
 
0.7%
900 385
38.6%
930 5
 
0.5%
1000 96
 
9.6%
1030 10
 
1.0%
1040 1
 
0.1%
1100 24
 
2.4%
1130 2
 
0.2%
ValueCountFrequency (%)
2000 11
 
1.1%
1900 136
13.6%
1850 3
 
0.3%
1840 1
 
0.1%
1830 11
 
1.1%
1800 4
 
0.4%
1730 1
 
0.1%
1700 7
 
0.7%
1640 1
 
0.1%
1630 2
 
0.2%

시간 마지막
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1586.8337
Minimum0
Maximum2300
Zeros132
Zeros (%)13.2%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T08:38:41.114932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11600
median1800
Q32100
95-th percentile2100
Maximum2300
Range2300
Interquartile range (IQR)500

Descriptive statistics

Standard deviation671.21859
Coefficient of variation (CV)0.42299241
Kurtosis1.2866801
Mean1586.8337
Median Absolute Deviation (MAD)300
Skewness-1.6206636
Sum1583660
Variance450534.4
MonotonicityNot monotonic
2024-05-11T08:38:41.824377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2100 277
27.8%
1800 255
25.6%
0 132
13.2%
1700 102
 
10.2%
1600 40
 
4.0%
2030 35
 
3.5%
1200 24
 
2.4%
2000 20
 
2.0%
1100 17
 
1.7%
1530 12
 
1.2%
Other values (24) 84
 
8.4%
ValueCountFrequency (%)
0 132
13.2%
900 6
 
0.6%
920 1
 
0.1%
1000 2
 
0.2%
1020 1
 
0.1%
1030 3
 
0.3%
1100 17
 
1.7%
1130 2
 
0.2%
1200 24
 
2.4%
1230 7
 
0.7%
ValueCountFrequency (%)
2300 1
 
0.1%
2200 6
 
0.6%
2130 2
 
0.2%
2100 277
27.8%
2050 3
 
0.3%
2040 1
 
0.1%
2030 35
 
3.5%
2000 20
 
2.0%
1900 8
 
0.8%
1830 2
 
0.2%

일정 타입
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9448898
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2024-05-11T08:38:42.275214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4
Maximum17
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6493445
Coefficient of variation (CV)1.362208
Kurtosis16.946099
Mean1.9448898
Median Absolute Deviation (MAD)0
Skewness4.046514
Sum1941
Variance7.019026
MonotonicityNot monotonic
2024-05-11T08:38:42.691844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 784
78.6%
4 95
 
9.5%
3 82
 
8.2%
14 14
 
1.4%
16 12
 
1.2%
11 6
 
0.6%
15 4
 
0.4%
17 1
 
0.1%
ValueCountFrequency (%)
1 784
78.6%
3 82
 
8.2%
4 95
 
9.5%
11 6
 
0.6%
14 14
 
1.4%
15 4
 
0.4%
16 12
 
1.2%
17 1
 
0.1%
ValueCountFrequency (%)
17 1
 
0.1%
16 12
 
1.2%
15 4
 
0.4%
14 14
 
1.4%
11 6
 
0.6%
4 95
 
9.5%
3 82
 
8.2%
1 784
78.6%

일정구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
행사일
784 
전시일
95 
강연일
82 
<NA>
 
37

Length

Max length4
Median length3
Mean length3.0370741
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행사일 784
78.6%
전시일 95
 
9.5%
강연일 82
 
8.2%
<NA> 37
 
3.7%

Length

2024-05-11T08:38:43.122633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:43.481491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행사일 784
78.6%
전시일 95
 
9.5%
강연일 82
 
8.2%
na 37
 
3.7%

주기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1
919 
2
 
70
3
 
8
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 919
92.1%
2 70
 
7.0%
3 8
 
0.8%
4 1
 
0.1%

Length

2024-05-11T08:38:43.910467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:44.232163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 919
92.1%
2 70
 
7.0%
3 8
 
0.8%
4 1
 
0.1%

주기명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
일
919 
주
 
70
월
 
8
년
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일 919
92.1%
주 70
 
7.0%
월 8
 
0.8%
년 1
 
0.1%

Length

2024-05-11T08:38:44.635373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:45.029503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일 919
92.1%
주 70
 
7.0%
월 8
 
0.8%
년 1
 
0.1%

주기 값
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
928 
화요일
 
21
목요일
 
12
금요일
 
11
토요일
 
10
Other values (3)
 
16

Length

Max length4
Median length4
Mean length3.9298597
Min length3

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> 928
93.0%
화요일 21
 
2.1%
목요일 12
 
1.2%
금요일 11
 
1.1%
토요일 10
 
1.0%
수요일 7
 
0.7%
일요일 6
 
0.6%
월요일 3
 
0.3%

Length

2024-05-11T08:38:45.754855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:46.141774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 928
93.0%
화요일 21
 
2.1%
목요일 12
 
1.2%
금요일 11
 
1.1%
토요일 10
 
1.0%
수요일 7
 
0.7%
일요일 6
 
0.6%
월요일 3
 
0.3%

후원자
Text

MISSING 

Distinct154
Distinct (%)19.6%
Missing214
Missing (%)21.4%
Memory size7.9 KiB
2024-05-11T08:38:46.956785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length5
Mean length7.9145408
Min length2

Characters and Unicode

Total characters6205
Distinct characters260
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

Unique99 ?
Unique (%)12.6%

Sample

1st row서울도서관
2nd row서울도서관
3rd row서울도서관
4th row서울도서관
5th row서울도서관
ValueCountFrequency (%)
서울도서관 620
57.6%
정보서비스과 26
 
2.4%
르네21 20
 
1.9%
독서대학 17
 
1.6%
도서관정책과 16
 
1.5%
서울시 10
 
0.9%
사단법인 9
 
0.8%
장날 9
 
0.8%
바꾸는 9
 
0.8%
하나 9
 
0.8%
Other values (159) 331
30.8%
2024-05-11T08:38:48.290992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 1443
23.3%
관 713
 
11.5%
울 706
 
11.4%
도 700
 
11.3%
306
 
4.9%
, 176
 
2.8%
사 73
 
1.2%
한 59
 
1.0%
국 57
 
0.9%
정 51
 
0.8%
Other values (250) 1921
31.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5602
90.3%
Space Separator 306
 
4.9%
Other Punctuation 185
 
3.0%
Decimal Number 43
 
0.7%
Uppercase Letter 26
 
0.4%
Lowercase Letter 15
 
0.2%
Close Punctuation 13
 
0.2%
Open Punctuation 13
 
0.2%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1443
25.8%
관 713
12.7%
울 706
12.6%
도 700
12.5%
사 73
 
1.3%
한 59
 
1.1%
국 57
 
1.0%
정 51
 
0.9%
과 50
 
0.9%
원 47
 
0.8%
Other values (215) 1703
30.4%
Lowercase Letter
ValueCountFrequency (%)
s 2
13.3%
w 2
13.3%
d 2
13.3%
b 2
13.3%
k 1
6.7%
t 1
6.7%
e 1
6.7%
i 1
6.7%
l 1
6.7%
r 1
6.7%
Uppercase Letter
ValueCountFrequency (%)
T 7
26.9%
B 6
23.1%
S 4
15.4%
V 3
11.5%
K 2
 
7.7%
O 2
 
7.7%
A 1
 
3.8%
C 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 176
95.1%
/ 7
 
3.8%
& 1
 
0.5%
. 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 21
48.8%
2 21
48.8%
3 1
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 11
84.6%
」 1
 
7.7%
] 1
 
7.7%
Open Punctuation
ValueCountFrequency (%)
( 11
84.6%
「 1
 
7.7%
[ 1
 
7.7%
Space Separator
ValueCountFrequency (%)
306
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5602
90.3%
Common 562
 
9.1%
Latin 41
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1443
25.8%
관 713
12.7%
울 706
12.6%
도 700
12.5%
사 73
 
1.3%
한 59
 
1.1%
국 57
 
1.0%
정 51
 
0.9%
과 50
 
0.9%
원 47
 
0.8%
Other values (215) 1703
30.4%
Latin
ValueCountFrequency (%)
T 7
17.1%
B 6
14.6%
S 4
9.8%
V 3
 
7.3%
s 2
 
4.9%
w 2
 
4.9%
d 2
 
4.9%
K 2
 
4.9%
O 2
 
4.9%
b 2
 
4.9%
Other values (9) 9
22.0%
Common
ValueCountFrequency (%)
306
54.4%
, 176
31.3%
1 21
 
3.7%
2 21
 
3.7%
) 11
 
2.0%
( 11
 
2.0%
/ 7
 
1.2%
+ 1
 
0.2%
& 1
 
0.2%
- 1
 
0.2%
Other values (6) 6
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5601
90.3%
ASCII 601
 
9.7%
None 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 1443
25.8%
관 713
12.7%
울 706
12.6%
도 700
12.5%
사 73
 
1.3%
한 59
 
1.1%
국 57
 
1.0%
정 51
 
0.9%
과 50
 
0.9%
원 47
 
0.8%
Other values (214) 1702
30.4%
ASCII
ValueCountFrequency (%)
306
50.9%
, 176
29.3%
1 21
 
3.5%
2 21
 
3.5%
) 11
 
1.8%
( 11
 
1.8%
/ 7
 
1.2%
T 7
 
1.2%
B 6
 
1.0%
S 4
 
0.7%
Other values (23) 31
 
5.2%
Compat Jamo
ValueCountFrequency (%)
ㅓ 1
100.0%
None
ValueCountFrequency (%)
」 1
50.0%
「 1
50.0%

장소
Text

MISSING 

Distinct193
Distinct (%)23.1%
Missing162
Missing (%)16.2%
Memory size7.9 KiB
2024-05-11T08:38:48.939034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length10.998804
Min length2

Characters and Unicode

Total characters9195
Distinct characters184
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)15.7%

Sample

1st row생각마루
2nd row생각마루
3rd row생각마루
4th row일반자료실 2층 전시서가
5th row서울도서관 생각마루
ValueCountFrequency (%)
서울도서관 404
21.1%
사서교육장 225
 
11.7%
기획전시실 144
 
7.5%
4층 131
 
6.8%
1층 99
 
5.2%
일반자료실 68
 
3.5%
자료실 57
 
3.0%
전시서가 53
 
2.8%
생각마루 47
 
2.5%
2층 38
 
2.0%
Other values (162) 652
34.0%
2024-05-11T08:38:50.486701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 1299
 
14.1%
1103
 
12.0%
울 499
 
5.4%
도 486
 
5.3%
관 469
 
5.1%
실 440
 
4.8%
층 364
 
4.0%
자 291
 
3.2%
장 288
 
3.1%
료 285
 
3.1%
Other values (174) 3671
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7313
79.5%
Space Separator 1103
 
12.0%
Decimal Number 576
 
6.3%
Other Punctuation 73
 
0.8%
Close Punctuation 57
 
0.6%
Open Punctuation 57
 
0.6%
Dash Punctuation 8
 
0.1%
Uppercase Letter 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1299
17.8%
울 499
 
6.8%
도 486
 
6.6%
관 469
 
6.4%
실 440
 
6.0%
층 364
 
5.0%
자 291
 
4.0%
장 288
 
3.9%
료 285
 
3.9%
시 251
 
3.4%
Other values (154) 2641
36.1%
Decimal Number
ValueCountFrequency (%)
1 208
36.1%
4 184
31.9%
2 123
21.4%
3 26
 
4.5%
6 21
 
3.6%
0 7
 
1.2%
5 4
 
0.7%
7 3
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
F 2
28.6%
B 2
28.6%
A 1
14.3%
H 1
14.3%
S 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 72
98.6%
. 1
 
1.4%
Space Separator
ValueCountFrequency (%)
1103
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7311
79.5%
Common 1875
 
20.4%
Latin 7
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1299
17.8%
울 499
 
6.8%
도 486
 
6.6%
관 469
 
6.4%
실 440
 
6.0%
층 364
 
5.0%
자 291
 
4.0%
장 288
 
3.9%
료 285
 
3.9%
시 251
 
3.4%
Other values (152) 2639
36.1%
Common
ValueCountFrequency (%)
1103
58.8%
1 208
 
11.1%
4 184
 
9.8%
2 123
 
6.6%
, 72
 
3.8%
) 57
 
3.0%
( 57
 
3.0%
3 26
 
1.4%
6 21
 
1.1%
- 8
 
0.4%
Other values (5) 16
 
0.9%
Latin
ValueCountFrequency (%)
F 2
28.6%
B 2
28.6%
A 1
14.3%
H 1
14.3%
S 1
14.3%
Han
ValueCountFrequency (%)
書 1
50.0%
愛 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7310
79.5%
ASCII 1882
 
20.5%
CJK 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 1299
17.8%
울 499
 
6.8%
도 486
 
6.6%
관 469
 
6.4%
실 440
 
6.0%
층 364
 
5.0%
자 291
 
4.0%
장 288
 
3.9%
료 285
 
3.9%
시 251
 
3.4%
Other values (151) 2638
36.1%
ASCII
ValueCountFrequency (%)
1103
58.6%
1 208
 
11.1%
4 184
 
9.8%
2 123
 
6.5%
, 72
 
3.8%
) 57
 
3.0%
( 57
 
3.0%
3 26
 
1.4%
6 21
 
1.1%
- 8
 
0.4%
Other values (10) 23
 
1.2%
Compat Jamo
ValueCountFrequency (%)
ㅏ 1
100.0%
CJK
ValueCountFrequency (%)
書 1
50.0%
愛 1
50.0%

시
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
550 
서울
442 
서울
 
2
서울 경기
 
2
서울경기
 
1

Length

Max length10
Median length4
Mean length3.1202405
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 550
55.1%
서울 442
44.3%
서울 2
 
0.2%
서울 경기 2
 
0.2%
서울경기 1
 
0.1%
서울광장,서울도서관 1
 
0.1%

Length

2024-05-11T08:38:51.141351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:51.751582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 550
55.0%
서울 446
44.6%
경기 2
 
0.2%
서울경기 1
 
0.1%
서울광장,서울도서관 1
 
0.1%

참고 URL
Text

MISSING 

Distinct101
Distinct (%)47.2%
Missing784
Missing (%)78.6%
Memory size7.9 KiB
2024-05-11T08:38:52.644526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length99
Median length74.5
Mean length42.873832
Min length2

Characters and Unicode

Total characters9175
Distinct characters73
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)35.0%

Sample

1st rowhttps://lib.seoul.go.kr/bbs/content/93_60155
2nd rowhttps://lib.seoul.go.kr/lecture/applyDetail/5042
3rd rowhttps://lib.seoul.go.kr/lecture/applyDetail/5002
4th rowhttps://lib.seoul.go.kr/bbs/content/93_59951
5th rowhttps://lib.seoul.go.kr/bbs/content/93_59756
ValueCountFrequency (%)
http://lib.seoul.go.kr/lecture/applylist 23
 
10.6%
https://lib.seoul.go.kr/rwww/html/ko/readingplaza.jsp 15
 
6.9%
http://lib.seoul.go.kr/bbs/content/3_19865 12
 
5.5%
www.facebook.com/bookstore.tour.seoul 11
 
5.1%
http://lib.seoul.go.kr/bbs/content/3_8631 8
 
3.7%
http://www.seoulbookmarket.com 6
 
2.8%
http://seoulphotofestival.com 5
 
2.3%
http://lib.seoul.go.kr/bbs/content/3_19527 5
 
2.3%
http://lib.seoul.go.kr/bbs/content/3_19097 5
 
2.3%
http://lib.seoul.go.kr/bbs/content/30_16098 5
 
2.3%
Other values (92) 122
56.2%
2024-05-11T08:38:54.145049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 939
 
10.2%
t 768
 
8.4%
o 668
 
7.3%
. 644
 
7.0%
l 512
 
5.6%
e 507
 
5.5%
s 435
 
4.7%
b 427
 
4.7%
p 324
 
3.5%
r 323
 
3.5%
Other values (63) 3628
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6205
67.6%
Other Punctuation 1811
 
19.7%
Decimal Number 880
 
9.6%
Uppercase Letter 121
 
1.3%
Connector Punctuation 116
 
1.3%
Math Symbol 23
 
0.3%
Other Letter 14
 
0.2%
Space Separator 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 768
12.4%
o 668
 
10.8%
l 512
 
8.3%
e 507
 
8.2%
s 435
 
7.0%
b 427
 
6.9%
p 324
 
5.2%
r 323
 
5.2%
i 270
 
4.4%
u 258
 
4.2%
Other values (14) 1713
27.6%
Uppercase Letter
ValueCountFrequency (%)
L 23
19.0%
D 17
14.0%
P 15
12.4%
Q 9
 
7.4%
R 7
 
5.8%
A 6
 
5.0%
S 5
 
4.1%
F 5
 
4.1%
Z 4
 
3.3%
G 4
 
3.3%
Other values (10) 26
21.5%
Decimal Number
ValueCountFrequency (%)
1 177
20.1%
3 155
17.6%
9 90
10.2%
0 90
10.2%
4 69
 
7.8%
5 66
 
7.5%
8 66
 
7.5%
2 61
 
6.9%
6 56
 
6.4%
7 50
 
5.7%
Other Letter
ValueCountFrequency (%)
서 3
21.4%
울 3
21.4%
사 1
 
7.1%
진 1
 
7.1%
축 1
 
7.1%
제 1
 
7.1%
新 1
 
7.1%
아 1
 
7.1%
리 1
 
7.1%
랑 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/ 939
51.8%
. 644
35.6%
: 200
 
11.0%
? 20
 
1.1%
& 8
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_ 116
100.0%
Math Symbol
ValueCountFrequency (%)
= 23
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6326
68.9%
Common 2835
30.9%
Hangul 13
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 768
12.1%
o 668
 
10.6%
l 512
 
8.1%
e 507
 
8.0%
s 435
 
6.9%
b 427
 
6.7%
p 324
 
5.1%
r 323
 
5.1%
i 270
 
4.3%
u 258
 
4.1%
Other values (34) 1834
29.0%
Common
ValueCountFrequency (%)
/ 939
33.1%
. 644
22.7%
: 200
 
7.1%
1 177
 
6.2%
3 155
 
5.5%
_ 116
 
4.1%
9 90
 
3.2%
0 90
 
3.2%
4 69
 
2.4%
5 66
 
2.3%
Other values (9) 289
 
10.2%
Hangul
ValueCountFrequency (%)
서 3
23.1%
울 3
23.1%
사 1
 
7.7%
진 1
 
7.7%
축 1
 
7.7%
제 1
 
7.7%
아 1
 
7.7%
리 1
 
7.7%
랑 1
 
7.7%
Han
ValueCountFrequency (%)
新 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9161
99.8%
Hangul 13
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 939
 
10.2%
t 768
 
8.4%
o 668
 
7.3%
. 644
 
7.0%
l 512
 
5.6%
e 507
 
5.5%
s 435
 
4.7%
b 427
 
4.7%
p 324
 
3.5%
r 323
 
3.5%
Other values (53) 3614
39.4%
Hangul
ValueCountFrequency (%)
서 3
23.1%
울 3
23.1%
사 1
 
7.7%
진 1
 
7.7%
축 1
 
7.7%
제 1
 
7.7%
아 1
 
7.7%
리 1
 
7.7%
랑 1
 
7.7%
CJK
ValueCountFrequency (%)
新 1
100.0%

일정 콘텐츠
Text

MISSING 

Distinct647
Distinct (%)67.3%
Missing37
Missing (%)3.7%
Memory size7.9 KiB
2024-05-11T08:38:55.126349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length304
Mean length81.01769
Min length1

Characters and Unicode

Total characters77858
Distinct characters900
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique547 ?
Unique (%)56.9%

Sample

1st row서울 문화의 밤 - 건축여행자 김예슬 작가와의 만남
2nd row서울 문화의 밤 - 역사수집가 박건호 작가와의 만남
3rd row어린이날 기념, 서울 문화의 밤 - 이지은 그림책 작가와의 만남
4th row[책피는 서울도서관] 북큐레이션 5월 - 전시주제: 우리에게 가족이란??????? - 전시내용 여러분들에게 가족은 어떤 존재인가요? 우린 익숙함에 속아 항상 곁에 있는 가족의 소중함을 잊고 지내곤 합니다. 이번 북큐레이션은 가족의 사랑과 소중함을 되새겨볼 수 있는 도서들을 선정해보았습니다. 가족관련 도서를 통해 서로를 이해하고 가족의 사랑과 감사를 느껴보는 시간을 가져보시기 바랍니다.
5th row2024년 서울야외도서관 : 책읽는 맑은냇가
ValueCountFrequency (%)
1030
 
5.8%
서울도서관 203
 
1.1%
전시 186
 
1.0%
및 154
 
0.9%
함께 144
 
0.8%
있는 123
 
0.7%
도서 115
 
0.6%
수 99
 
0.6%
다양한 92
 
0.5%
책 92
 
0.5%
Other values (5520) 15485
87.4%
2024-05-11T08:38:56.761684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19705
25.3%
서 1968
 
2.5%
시 1220
 
1.6%
의 1032
 
1.3%
도 1014
 
1.3%
는 824
 
1.1%
이 808
 
1.0%
을 806
 
1.0%
관 761
 
1.0%
, 739
 
0.9%
Other values (890) 48981
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48333
62.1%
Space Separator 19705
25.3%
Decimal Number 3392
 
4.4%
Other Punctuation 2769
 
3.6%
Lowercase Letter 1017
 
1.3%
Close Punctuation 572
 
0.7%
Open Punctuation 567
 
0.7%
Dash Punctuation 453
 
0.6%
Uppercase Letter 416
 
0.5%
Math Symbol 373
 
0.5%
Other values (5) 261
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1968
 
4.1%
시 1220
 
2.5%
의 1032
 
2.1%
도 1014
 
2.1%
는 824
 
1.7%
이 808
 
1.7%
을 806
 
1.7%
관 761
 
1.6%
한 721
 
1.5%
전 706
 
1.5%
Other values (785) 38473
79.6%
Uppercase Letter
ValueCountFrequency (%)
S 48
11.5%
T 47
11.3%
B 40
 
9.6%
V 30
 
7.2%
E 29
 
7.0%
D 29
 
7.0%
A 21
 
5.0%
N 21
 
5.0%
G 20
 
4.8%
R 18
 
4.3%
Other values (15) 113
27.2%
Lowercase Letter
ValueCountFrequency (%)
o 105
 
10.3%
r 102
 
10.0%
e 99
 
9.7%
i 80
 
7.9%
s 75
 
7.4%
a 69
 
6.8%
t 57
 
5.6%
n 54
 
5.3%
l 48
 
4.7%
k 44
 
4.3%
Other values (14) 284
27.9%
Other Punctuation
ValueCountFrequency (%)
, 739
26.7%
: 635
22.9%
. 619
22.4%
' 339
12.2%
? 174
 
6.3%
/ 115
 
4.2%
! 81
 
2.9%
* 36
 
1.3%
※ 10
 
0.4%
& 6
 
0.2%
Other values (4) 15
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 738
21.8%
2 670
19.8%
0 654
19.3%
4 274
 
8.1%
3 268
 
7.9%
5 240
 
7.1%
6 204
 
6.0%
9 127
 
3.7%
7 115
 
3.4%
8 102
 
3.0%
Math Symbol
ValueCountFrequency (%)
~ 136
36.5%
< 104
27.9%
> 103
27.6%
= 15
 
4.0%
× 4
 
1.1%
∞ 4
 
1.1%
→ 4
 
1.1%
+ 3
 
0.8%
Other Symbol
ValueCountFrequency (%)
○ 39
43.8%
▶ 15
 
16.9%
★ 15
 
16.9%
□ 13
 
14.6%
☞ 5
 
5.6%
☜ 2
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 460
80.4%
』 43
 
7.5%
] 32
 
5.6%
」 25
 
4.4%
》 12
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 455
80.2%
『 43
 
7.6%
[ 32
 
5.6%
「 25
 
4.4%
《 12
 
2.1%
Final Punctuation
ValueCountFrequency (%)
’ 49
89.1%
” 6
 
10.9%
Initial Punctuation
ValueCountFrequency (%)
‘ 48
88.9%
“ 6
 
11.1%
Space Separator
ValueCountFrequency (%)
19705
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 453
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 33
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48260
62.0%
Common 28092
36.1%
Latin 1433
 
1.8%
Han 73
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1968
 
4.1%
시 1220
 
2.5%
의 1032
 
2.1%
도 1014
 
2.1%
는 824
 
1.7%
이 808
 
1.7%
을 806
 
1.7%
관 761
 
1.6%
한 721
 
1.5%
전 706
 
1.5%
Other values (762) 38400
79.6%
Common
ValueCountFrequency (%)
19705
70.1%
, 739
 
2.6%
1 738
 
2.6%
2 670
 
2.4%
0 654
 
2.3%
: 635
 
2.3%
. 619
 
2.2%
) 460
 
1.6%
( 455
 
1.6%
- 453
 
1.6%
Other values (46) 2964
 
10.6%
Latin
ValueCountFrequency (%)
o 105
 
7.3%
r 102
 
7.1%
e 99
 
6.9%
i 80
 
5.6%
s 75
 
5.2%
a 69
 
4.8%
t 57
 
4.0%
n 54
 
3.8%
S 48
 
3.3%
l 48
 
3.3%
Other values (39) 696
48.6%
Han
ValueCountFrequency (%)
展 32
43.8%
書 6
 
8.2%
路 6
 
8.2%
休 4
 
5.5%
詩 3
 
4.1%
讀 2
 
2.7%
知 2
 
2.7%
好 2
 
2.7%
樂 2
 
2.7%
種 1
 
1.4%
Other values (13) 13
17.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48190
61.9%
ASCII 29143
37.4%
None 166
 
0.2%
Punctuation 119
 
0.2%
CJK 71
 
0.1%
Compat Jamo 70
 
0.1%
Geometric Shapes 67
 
0.1%
Misc Symbols 22
 
< 0.1%
Math Operators 4
 
< 0.1%
Arrows 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19705
67.6%
, 739
 
2.5%
1 738
 
2.5%
2 670
 
2.3%
0 654
 
2.2%
: 635
 
2.2%
. 619
 
2.1%
) 460
 
1.6%
( 455
 
1.6%
- 453
 
1.6%
Other values (74) 4015
 
13.8%
Hangul
ValueCountFrequency (%)
서 1968
 
4.1%
시 1220
 
2.5%
의 1032
 
2.1%
도 1014
 
2.1%
는 824
 
1.7%
이 808
 
1.7%
을 806
 
1.7%
관 761
 
1.6%
한 721
 
1.5%
전 706
 
1.5%
Other values (759) 38330
79.5%
Compat Jamo
ValueCountFrequency (%)
ㅇ 67
95.7%
ㅁ 2
 
2.9%
ㅣ 1
 
1.4%
Punctuation
ValueCountFrequency (%)
’ 49
41.2%
‘ 48
40.3%
※ 10
 
8.4%
“ 6
 
5.0%
” 6
 
5.0%
None
ValueCountFrequency (%)
』 43
25.9%
『 43
25.9%
」 25
15.1%
「 25
15.1%
《 12
 
7.2%
》 12
 
7.2%
× 4
 
2.4%
＊ 2
 
1.2%
Geometric Shapes
ValueCountFrequency (%)
○ 39
58.2%
▶ 15
 
22.4%
□ 13
 
19.4%
CJK
ValueCountFrequency (%)
展 32
45.1%
書 6
 
8.5%
路 6
 
8.5%
休 4
 
5.6%
詩 3
 
4.2%
讀 2
 
2.8%
知 2
 
2.8%
好 2
 
2.8%
種 1
 
1.4%
圖 1
 
1.4%
Other values (12) 12
 
16.9%
Misc Symbols
ValueCountFrequency (%)
★ 15
68.2%
☞ 5
 
22.7%
☜ 2
 
9.1%
Math Operators
ValueCountFrequency (%)
∞ 4
100.0%
Arrows
ValueCountFrequency (%)
→ 4
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
樂 2
100.0%

Interactions

2024-05-11T08:38:29.489218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:17.034293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:19.939683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:22.415821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:24.805712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:27.358903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:29.936360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:17.369457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:20.340831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:22.850225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:25.122852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:27.719792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:30.323186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:17.999269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:20.720894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:23.173741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:25.488374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:28.096940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:30.933845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:18.447877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:21.180352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:23.514095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:25.771616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:28.495898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:31.290702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:18.864687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:21.715708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:24.020173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:26.591500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:28.822676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:31.703640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:19.239326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:21.998501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:24.412239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:26.965031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:38:29.138132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T08:38:57.221583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일정 아이디날짜 처음날짜 마지막시간 처음시간 마지막일정 타입일정구분주기주기명주기 값시
일정 아이디1.0000.981NaN0.4940.4620.8400.5960.2290.2290.5290.569
날짜 처음0.9811.000NaN0.5190.4760.8140.5330.2430.2430.6380.219
날짜 마지막NaNNaN1.000NaNNaNNaNNaNNaNNaNNaNNaN
시간 처음0.4940.519NaN1.0000.9380.1190.3040.2140.2140.6950.193
시간 마지막0.4620.476NaN0.9381.0000.2800.4210.1440.1440.7610.000
일정 타입0.8400.814NaN0.1190.2801.0001.0000.0000.0000.2770.053
일정구분0.5960.533NaN0.3040.4211.0001.0000.0340.0340.3560.089
주기0.2290.243NaN0.2140.1440.0000.0341.0001.000NaN0.000
주기명0.2290.243NaN0.2140.1440.0000.0341.0001.000NaN0.000
주기 값0.5290.638NaN0.6950.7610.2770.356NaNNaN1.0000.000
시0.5690.219NaN0.1930.0000.0530.0890.0000.0000.0001.000
2024-05-11T08:38:57.692156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일정구분주기주기 값주기명시
일정구분1.0000.0320.2460.0320.066
주기0.0321.0001.0001.0000.000
주기 값0.2461.0001.0001.0000.000
주기명0.0321.0001.0001.0000.000
시0.0660.0000.0000.0001.000
2024-05-11T08:38:58.120559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일정 아이디날짜 처음날짜 마지막시간 처음시간 마지막일정 타입일정구분주기주기명주기 값시
일정 아이디1.0000.9990.9960.0220.2350.1960.4380.1380.1380.3060.269
날짜 처음0.9991.0000.9970.0280.2330.1950.3760.1470.1470.2650.135
날짜 마지막0.9960.9971.0000.0260.2320.1940.0000.0000.0001.0000.000
시간 처음0.0220.0280.0261.0000.3690.0810.2020.0970.0970.3040.119
시간 마지막0.2350.2330.2320.3691.000-0.1870.2950.0650.0650.3570.000
일정 타입0.1960.1950.1940.081-0.1871.0000.9990.0000.0000.2840.065
일정구분0.4380.3760.0000.2020.2950.9991.0000.0320.0320.2460.066
주기0.1380.1470.0000.0970.0650.0000.0321.0001.0001.0000.000
주기명0.1380.1470.0000.0970.0650.0000.0321.0001.0001.0000.000
주기 값0.3060.2651.0000.3040.3570.2840.2461.0001.0001.0000.000
시0.2690.1350.0000.1190.0000.0650.0660.0000.0000.0001.000

Missing values

2024-05-11T08:38:32.429848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T08:38:33.551355image/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.
2024-05-11T08:38:34.221878image/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

일정 아이디일정 제목날짜 처음날짜 마지막시간 처음시간 마지막일정 타입일정구분주기주기명주기 값후원자장소시참고 URL일정 콘텐츠
07442책읽는 서울광장20240531202405311000170014<NA>1일<NA><NA><NA><NA><NA><NA>
17476책읽는 맑은냇가20240531202405311000170016<NA>1일<NA><NA><NA><NA><NA><NA>
27441책읽는 서울광장20240530202405301000170014<NA>1일<NA><NA><NA><NA><NA><NA>
37440책읽는 서울광장20240526202405261000170014<NA>1일<NA><NA><NA><NA><NA><NA>
47510광화문 야외마당20240526202405261000170011<NA>1일<NA><NA><NA><NA><NA><NA>
57445책읽는 맑은냇가20240525202405251000170016<NA>1일<NA><NA><NA><NA><NA><NA>
67527광화문 야외마당20240525202405251000170011<NA>1일<NA><NA><NA><NA><NA><NA>
77439책읽는 서울광장20240525202405251000170014<NA>1일<NA><NA><NA><NA><NA><NA>
87514작가와의 만남(김예슬)2024052420240524190020303강연일1일<NA><NA>생각마루서울<NA>서울 문화의 밤 - 건축여행자 김예슬 작가와의 만남
97444책읽는 맑은냇가20240524202405241000170016<NA>1일<NA><NA><NA><NA><NA><NA>
일정 아이디일정 제목날짜 처음날짜 마지막시간 처음시간 마지막일정 타입일정구분주기주기명주기 값후원자장소시참고 URL일정 콘텐츠
988243[강연] 경성의 풍속도와 염상섭 소설2012111620121116150017001행사일1일<NA>경향신문사서울도서관 사서교육장(4층)<NA><NA>기획전시 '2012 염상섭 문화제' 관련 행사 21세기 독자, 염상섭을 만나다. 1920-30년대 경성의 문화와 풍속도에 비춰 염상섭의 소설을 함께 읽어본다. 사회 : 류보선 군산대 교수 출연 : 이경훈 연세대 교수, 심진경 문학평론가, 이혜령 성균관대 교수
989261낭독봉사의 방법 강의 안내2012111520121115183020001행사일1일<NA>서울도서관서울도서관 4층 사서교육장<NA><NA>강의주제 : 낭독봉사의 방법 강사 : KBS아나운서 배창복 대상 : 장애인 자료실 자원봉사자 및 관심있는 도서관 이용자, 직원 많은 참여바랍니다
990245[강의] 고전강독회 - 논어의 교훈2012111420121114150017001행사일1일<NA>한국출판문화산업진흥원 주최, 서울도서관 주관서울도서관 사서교육장(4층)<NA>http://yeyak.seoul.go.kr강사 : 심재호 고려대학교 한문학 교수 논어의 일부 원문을 되읽으면서 그 현재적 가치를 탐색한다.
991242[공연] 모던걸 모던보이, 염상섭을 읽다2012111020121110180001행사일1일<NA>경향신문사서울광장<NA><NA>음악,영상,퍼포먼스를 종횡무진하는 복합장르 공연. 근대문화와 현대예술의 만남을 통해 서울의 과거로 떠나는 시간여행. 40명의 모던걸, 모던보이가 태블릿 PC로 염상섭의 소설을 읽으면서 서울광장을 거니는 퍼포먼스로 막을 연다. 이어 1920-30년대를 풍미한 재즈와 민요가 연주되고, 염상섭의 소설에서 받은 감흥이 현대음악으로 새롭게 태어난다.
992241[강연]내가 읽은 선배 작가 염상섭- 현기영, 조경란, 전성태 소설가2012110920121109150017001행사일1일<NA>경향신문사서울도서관 사서교육장(4층)<NA><NA>기획전시 2012 염상섭 문학제 관련 행사 '21세기 독자, 염상섭을 만나다' 현역 작가들이 자신이 읽은 염상섭 작품의 독서 경험을 관객들에게 들려준다 -내가 읽은 선배 작가 염상섭 사회 : 강유정 문학평론가 출연 : 현기영, 조경란, 전성태 소설가
993223서울 북 페스티벌2012102620121028001행사일1일<NA>서울시서울도서관 및 서울광장 일대서울http://lib.seoul.go.kr/www/html/ko/bookFastival.jsp도서전시, 저자와의 만남, 독서토론, 문화체험행사 등
994222서울도서관 개관식2012102620121026163018201행사일1일<NA>서울도서관서울도서관서울광장,서울도서관<NA>1. 식전 행사(16:30~17:00) : 기념공연(오감만족콘서트) 2. 좌담회(17:00~17:50): 개관 영상물 상영(추진경과, 시설안내),의견청취 좌담회(서울도서관에 바란다) 3. 개관 행사(17:50~18:20):현판 제막식, 서울도서관 관람
995221[정책토론회]서울, 도서관을 말하다2012101320121013140016001행사일1일<NA>서울도서관 도서관정책과일반자료실 연결계단서울<NA>1.개요 '서울도서관' 개관에 즈음하여 시민들과 관련 전문가와 함께 우리시 도서관과 독서 문화 정책에 대해 논의하는 정책토론회를 개최함 2.주제 '서울, 도서관을 말하다' 발표: 2명(김태희 시의원, 이용훈 대표도서관건립추진반장) 3.토론 김기영(연세대 문헌정보학과 교수) 차성종(문체부 도서관정책과 사무관) 안찬수(책읽는 사회문화재단 사무처장) 공유선(한국어린이도서관협회 상임이사) 4.주요내용: 도서관 및 독서문화 활성화 방안 논의 서울시 도서관 및 독서문화 활성화 종합계획 소개 도서관 현안 공유와 개선방안, 정책제안 등 논의 5.진행순서 14:00 시작공연: 서대문구 글로리아 오케스트라단 14:15 서울도서관 추진경위 및 토론회 안내 14:20 주제발표 '서울, 도서관을 말하다' (김태희 서울시의원, 이용훈 대표도서관건립추진반장) 토론 (김기영, 차성종, 안찬수, 공유선) 사회 및 진행 (이인경 책나라연대 총무) 15:10 Intermission 15:20 청중토론, 정책제언 / 질의응답 16:10 서울도서관 둘러보기
996202시민과 함께 만드는 서울도서관2012092420120925100012001행사일1일<NA>서울도서관 정보서비스과서울도서관<NA><NA>1.개요 도서배가 및 장서점검 등 서울도서관 개관준비 작업을 시민들과 함께 함으로서 시민과 함께 만들고, 함께 누리는 서울도서관으로 자리매김 하고자 함 2.대상 일반자료실1, 일반자료실2, 서울자료실, 세계자료실, 보존서고 등 도서 20만여권 3.장소 서울도서관 4.작업내용 및 방법 오배가 자료를 재배가 청구기호, 레이블 오류 도서 색출 자료검수 및 비도서 배가 5.기타 일정 서울도서관 투어 및 교육
997301서울도서관 행사2012091720120921001행사일1일<NA>서울도서관서울도서관 앞 서울광장서울http://lib.seoul.go.kr참고URL 링크 안되네요~ 수정해주세요 첨부파일 아래에 '이미지파일만 첨부하세요' 문구 추가해주세요