Overview

Dataset statistics

Number of variables19
Number of observations1384
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
Duplicate rows (%)0.9%
Total size in memory220.4 KiB
Average record size in memory163.1 B

Variable types

Categorical7
Text1
Numeric10
DateTime1

Dataset

Description경기도 화성시 화성국민체육센터, 화성그린환경센터, 화성남부체육센터, 동탄중앙어울림센터, 반월체육센터의 연령별 이용현황입니다. 프로그램명, 강습요일, 시간, 장소, 정원 등을 확인할 수 있습니다.
Author화성도시공사
URLhttps://www.data.go.kr/data/15126949/fileData.do

Alerts

데이터기준일 has constant value ""Constant
Dataset has 12 (0.9%) duplicate rowsDuplicates
정원 is highly overall correlated with 강습요일High correlation
0-9세 is highly overall correlated with 10-19세 and 4 other fieldsHigh correlation
10-19세 is highly overall correlated with 0-9세High correlation
20-29세 is highly overall correlated with 30-39세 and 1 other fieldsHigh correlation
30-39세 is highly overall correlated with 0-9세 and 3 other fieldsHigh correlation
40-49세 is highly overall correlated with 0-9세 and 2 other fieldsHigh correlation
50-59세 is highly overall correlated with 0-9세 and 4 other fieldsHigh correlation
60-69세 is highly overall correlated with 0-9세 and 3 other fieldsHigh correlation
70-79세 is highly overall correlated with 60-69세 and 1 other fieldsHigh correlation
80-89세 is highly overall correlated with 90세 이상High correlation
센터명 is highly overall correlated with 시간 and 1 other fieldsHigh correlation
강습요일 is highly overall correlated with 정원High correlation
시간 is highly overall correlated with 센터명 and 1 other fieldsHigh correlation
대상 is highly overall correlated with 시간High correlation
구분 is highly overall correlated with 센터명High correlation
90세 이상 is highly overall correlated with 20-29세 and 4 other fieldsHigh correlation
강습요일 is highly imbalanced (62.2%)Imbalance
장소 is highly imbalanced (70.4%)Imbalance
구분 is highly imbalanced (71.1%)Imbalance
90세 이상 is highly imbalanced (98.7%)Imbalance
20-29세 is highly skewed (γ1 = 31.99836012)Skewed
30-39세 is highly skewed (γ1 = 22.88542379)Skewed
0-9세 has 1145 (82.7%) zerosZeros
10-19세 has 823 (59.5%) zerosZeros
20-29세 has 572 (41.3%) zerosZeros
30-39세 has 339 (24.5%) zerosZeros
40-49세 has 264 (19.1%) zerosZeros
50-59세 has 254 (18.4%) zerosZeros
60-69세 has 415 (30.0%) zerosZeros
70-79세 has 997 (72.0%) zerosZeros
80-89세 has 1308 (94.5%) zerosZeros

Reproduction

Analysis started2024-03-14 10:54:59.118054
Analysis finished2024-03-14 10:55:25.481225
Duration26.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

센터명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
반월체육센터
428 
화성남부체육센터
322 
동탄중앙어울림센터
305 
화성국민체육센터
279 
화성그린환경센터
50 

Length

Max length9
Median length8
Mean length7.6018786
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
반월체육센터 428
30.9%
화성남부체육센터 322
23.3%
동탄중앙어울림센터 305
22.0%
화성국민체육센터 279
20.2%
화성그린환경센터 50
 
3.6%

Length

2024-03-14T19:55:25.600876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:55:25.798081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
반월체육센터 428
30.9%
화성남부체육센터 322
23.3%
동탄중앙어울림센터 305
22.0%
화성국민체육센터 279
20.2%
화성그린환경센터 50
 
3.6%
Distinct1072
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
2024-03-14T19:55:26.650295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length22
Mean length15.742052
Min length2

Characters and Unicode

Total characters21787
Distinct characters140
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1056 ?
Unique (%)76.3%

Sample

1st row10시 그룹웨이트트레이닝A
2nd row10시 그룹웨이트트레이닝B
3rd row10시 서킷트레이닝A
4th row11시 그룹웨이트트레이닝A
5th row14시 그룹웨이트트레이닝A
ValueCountFrequency (%)
성인수영(저녁 70
 
3.3%
성인수영(새벽 62
 
2.9%
아쿠아로빅 33
 
1.5%
06시_수영_화 31
 
1.4%
성인수영(오전 30
 
1.4%
필라테스 27
 
1.3%
성인 26
 
1.2%
20시_수영_화 25
 
1.2%
10시_수영_화 24
 
1.1%
어린이수영 23
 
1.1%
Other values (669) 1795
83.6%
2024-03-14T19:55:27.790257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 1977
 
9.1%
1 1327
 
6.1%
1289
 
5.9%
1145
 
5.3%
1088
 
5.0%
878
 
4.0%
793
 
3.6%
772
 
3.5%
756
 
3.5%
( 697
 
3.2%
Other values (130) 11065
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12032
55.2%
Decimal Number 4108
 
18.9%
Connector Punctuation 1977
 
9.1%
Space Separator 1088
 
5.0%
Open Punctuation 861
 
4.0%
Close Punctuation 856
 
3.9%
Uppercase Letter 321
 
1.5%
Dash Punctuation 241
 
1.1%
Math Symbol 154
 
0.7%
Other Symbol 145
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1289
 
10.7%
1145
 
9.5%
878
 
7.3%
793
 
6.6%
772
 
6.4%
756
 
6.3%
614
 
5.1%
397
 
3.3%
396
 
3.3%
381
 
3.2%
Other values (104) 4611
38.3%
Decimal Number
ValueCountFrequency (%)
1 1327
32.3%
0 635
15.5%
2 362
 
8.8%
9 331
 
8.1%
6 316
 
7.7%
7 306
 
7.4%
5 251
 
6.1%
3 246
 
6.0%
4 229
 
5.6%
8 105
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
A 153
47.7%
B 144
44.9%
T 11
 
3.4%
P 11
 
3.4%
C 2
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 697
81.0%
[ 164
 
19.0%
Close Punctuation
ValueCountFrequency (%)
) 692
80.8%
] 164
 
19.2%
Math Symbol
ValueCountFrequency (%)
147
95.5%
~ 7
 
4.5%
Connector Punctuation
ValueCountFrequency (%)
_ 1977
100.0%
Space Separator
ValueCountFrequency (%)
1088
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 241
100.0%
Other Symbol
ValueCountFrequency (%)
145
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12032
55.2%
Common 9434
43.3%
Latin 321
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1289
 
10.7%
1145
 
9.5%
878
 
7.3%
793
 
6.6%
772
 
6.4%
756
 
6.3%
614
 
5.1%
397
 
3.3%
396
 
3.3%
381
 
3.2%
Other values (104) 4611
38.3%
Common
ValueCountFrequency (%)
_ 1977
21.0%
1 1327
14.1%
1088
11.5%
( 697
 
7.4%
) 692
 
7.3%
0 635
 
6.7%
2 362
 
3.8%
9 331
 
3.5%
6 316
 
3.3%
7 306
 
3.2%
Other values (11) 1703
18.1%
Latin
ValueCountFrequency (%)
A 153
47.7%
B 144
44.9%
T 11
 
3.4%
P 11
 
3.4%
C 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12032
55.2%
ASCII 9463
43.4%
Geometric Shapes 292
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 1977
20.9%
1 1327
14.0%
1088
11.5%
( 697
 
7.4%
) 692
 
7.3%
0 635
 
6.7%
2 362
 
3.8%
9 331
 
3.5%
6 316
 
3.3%
7 306
 
3.2%
Other values (14) 1732
18.3%
Hangul
ValueCountFrequency (%)
1289
 
10.7%
1145
 
9.5%
878
 
7.3%
793
 
6.6%
772
 
6.4%
756
 
6.3%
614
 
5.1%
397
 
3.3%
396
 
3.3%
381
 
3.2%
Other values (104) 4611
38.3%
Geometric Shapes
ValueCountFrequency (%)
147
50.3%
145
49.7%

강습요일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
월수금
685 
화목
650 
월화수목금
 
24
월화수목금토
 
15
월수
 
3
Other values (5)
 
7

Length

Max length7
Median length6
Mean length2.5982659
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row월수금
2nd row화목
3rd row월수금
4th row월수금
5th row월수금

Common Values

ValueCountFrequency (%)
월수금 685
49.5%
화목 650
47.0%
월화수목금 24
 
1.7%
월화수목금토 15
 
1.1%
월수 3
 
0.2%
월수목금 2
 
0.1%
월~토 2
 
0.1%
화목토 1
 
0.1%
월화수목금토일 1
 
0.1%
1
 
0.1%

Length

2024-03-14T19:55:28.030050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:55:28.255609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
월수금 685
49.5%
화목 650
47.0%
월화수목금 24
 
1.7%
월화수목금토 15
 
1.1%
월수 3
 
0.2%
월수목금 2
 
0.1%
월~토 2
 
0.1%
화목토 1
 
0.1%
월화수목금토일 1
 
0.1%
1
 
0.1%

시간
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
10:00
132 
07:00
130 
06:00
128 
09:00
124 
20:00
112 
Other values (27)
758 

Length

Max length11
Median length5
Mean length6.6026012
Min length4

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row10:00
2nd row10:00
3rd row10:00
4th row11:00
5th row14:00

Common Values

ValueCountFrequency (%)
10:00 132
 
9.5%
07:00 130
 
9.4%
06:00 128
 
9.2%
09:00 124
 
9.0%
20:00 112
 
8.1%
19:00 107
 
7.7%
17:00 87
 
6.3%
16:00 79
 
5.7%
19:00~19:50 69
 
5.0%
20:00~20:50 58
 
4.2%
Other values (22) 358
25.9%

Length

2024-03-14T19:55:28.550320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:00 132
 
9.5%
07:00 130
 
9.4%
06:00 128
 
9.2%
09:00 124
 
9.0%
20:00 112
 
8.1%
19:00 107
 
7.7%
17:00 87
 
6.3%
16:00 79
 
5.7%
19:00~19:50 69
 
5.0%
20:00~20:50 58
 
4.2%
Other values (22) 358
25.9%

장소
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
수영장
1177 
다목적실
 
92
체력단련실
 
27
다목적체육관
 
18
온돌강의실
 
18
Other values (5)
 
52

Length

Max length8
Median length3
Mean length3.2391618
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row체력단련실
2nd row체력단련실
3rd row수영장
4th row체력단련실
5th row체력단련실

Common Values

ValueCountFrequency (%)
수영장 1177
85.0%
다목적실 92
 
6.6%
체력단련실 27
 
2.0%
다목적체육관 18
 
1.3%
온돌강의실 18
 
1.3%
G.X room 16
 
1.2%
댄스실 16
 
1.2%
G.X룸 15
 
1.1%
헬스장 4
 
0.3%
탁구장 1
 
0.1%

Length

2024-03-14T19:55:28.818122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:55:29.212624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영장 1177
84.1%
다목적실 92
 
6.6%
체력단련실 27
 
1.9%
다목적체육관 18
 
1.3%
온돌강의실 18
 
1.3%
g.x 16
 
1.1%
room 16
 
1.1%
댄스실 16
 
1.1%
g.x룸 15
 
1.1%
헬스장 4
 
0.3%

정원
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.174855
Minimum4
Maximum450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:29.433113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile25
Q125
median25
Q325
95-th percentile50
Maximum450
Range446
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.735509
Coefficient of variation (CV)0.66497267
Kurtosis245.64966
Mean28.174855
Median Absolute Deviation (MAD)0
Skewness13.603603
Sum38994
Variance351.01929
MonotonicityNot monotonic
2024-03-14T19:55:29.628617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
25 1057
76.4%
30 201
 
14.5%
50 34
 
2.5%
20 20
 
1.4%
10 18
 
1.3%
60 16
 
1.2%
80 12
 
0.9%
15 5
 
0.4%
55 4
 
0.3%
40 4
 
0.3%
Other values (10) 13
 
0.9%
ValueCountFrequency (%)
4 2
 
0.1%
10 18
 
1.3%
15 5
 
0.4%
20 20
 
1.4%
24 1
 
0.1%
25 1057
76.4%
26 2
 
0.1%
30 201
 
14.5%
40 4
 
0.3%
50 34
 
2.5%
ValueCountFrequency (%)
450 1
 
0.1%
300 1
 
0.1%
250 1
 
0.1%
230 1
 
0.1%
170 1
 
0.1%
150 2
 
0.1%
100 1
 
0.1%
80 12
0.9%
60 16
1.2%
55 4
 
0.3%

대상
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
성인/청소년
768 
청소년/성인
203 
초등학생
200 
성인
158 
어린이
 
33
Other values (6)
 
22

Length

Max length10
Median length6
Mean length5.2232659
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row청소년/성인
2nd row청소년/성인
3rd row청소년/성인
4th row청소년/성인
5th row성인/청소년

Common Values

ValueCountFrequency (%)
성인/청소년 768
55.5%
청소년/성인 203
 
14.7%
초등학생 200
 
14.5%
성인 158
 
11.4%
어린이 33
 
2.4%
성인/청소년/어린이 12
 
0.9%
초등(1~6년) 3
 
0.2%
<NA> 2
 
0.1%
초등학생/중학생 2
 
0.1%
초등5년~중학생 2
 
0.1%

Length

2024-03-14T19:55:29.947563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성인/청소년 768
55.5%
청소년/성인 203
 
14.7%
초등학생 200
 
14.5%
성인 158
 
11.4%
어린이 33
 
2.4%
성인/청소년/어린이 12
 
0.9%
초등(1~6년 3
 
0.2%
na 2
 
0.1%
초등학생/중학생 2
 
0.1%
초등5년~중학생 2
 
0.1%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
구분없음
1170 
중급반
 
82
상급반
 
77
초급반
 
16
상급
 
11
Other values (5)
 
28

Length

Max length4
Median length4
Mean length3.8309249
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
구분없음 1170
84.5%
중급반 82
 
5.9%
상급반 77
 
5.6%
초급반 16
 
1.2%
상급 11
 
0.8%
기초반 9
 
0.7%
중급 9
 
0.7%
마스터 8
 
0.6%
마스터반 1
 
0.1%
초급 1
 
0.1%

Length

2024-03-14T19:55:30.189229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:55:30.417761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구분없음 1170
84.5%
중급반 82
 
5.9%
상급반 77
 
5.6%
초급반 16
 
1.2%
상급 11
 
0.8%
기초반 9
 
0.7%
중급 9
 
0.7%
마스터 8
 
0.6%
마스터반 1
 
0.1%
초급 1
 
0.1%

0-9세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2991329
Minimum0
Maximum96
Zeros1145
Zeros (%)82.7%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:30.711507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14
Maximum96
Range96
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.5269657
Coefficient of variation (CV)3.2738279
Kurtosis49.821576
Mean2.2991329
Median Absolute Deviation (MAD)0
Skewness5.9582475
Sum3182
Variance56.655213
MonotonicityNot monotonic
2024-03-14T19:55:31.152389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 1145
82.7%
6 20
 
1.4%
7 19
 
1.4%
5 17
 
1.2%
8 15
 
1.1%
4 15
 
1.1%
13 13
 
0.9%
3 12
 
0.9%
11 12
 
0.9%
10 12
 
0.9%
Other values (36) 104
 
7.5%
ValueCountFrequency (%)
0 1145
82.7%
1 5
 
0.4%
2 9
 
0.7%
3 12
 
0.9%
4 15
 
1.1%
5 17
 
1.2%
6 20
 
1.4%
7 19
 
1.4%
8 15
 
1.1%
9 11
 
0.8%
ValueCountFrequency (%)
96 1
0.1%
86 1
0.1%
85 1
0.1%
59 1
0.1%
58 1
0.1%
56 1
0.1%
50 1
0.1%
45 1
0.1%
42 1
0.1%
41 1
0.1%

10-19세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct84
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7550578
Minimum0
Maximum229
Zeros823
Zeros (%)59.5%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:31.556765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile41
Maximum229
Range229
Interquartile range (IQR)2

Descriptive statistics

Standard deviation21.387314
Coefficient of variation (CV)3.1661185
Kurtosis46.256687
Mean6.7550578
Median Absolute Deviation (MAD)0
Skewness6.0372943
Sum9349
Variance457.41718
MonotonicityNot monotonic
2024-03-14T19:55:31.975416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 823
59.5%
1 167
 
12.1%
2 73
 
5.3%
3 48
 
3.5%
4 25
 
1.8%
11 11
 
0.8%
13 10
 
0.7%
5 9
 
0.7%
9 9
 
0.7%
12 9
 
0.7%
Other values (74) 200
 
14.5%
ValueCountFrequency (%)
0 823
59.5%
1 167
 
12.1%
2 73
 
5.3%
3 48
 
3.5%
4 25
 
1.8%
5 9
 
0.7%
6 6
 
0.4%
7 6
 
0.4%
8 8
 
0.6%
9 9
 
0.7%
ValueCountFrequency (%)
229 1
0.1%
224 1
0.1%
214 1
0.1%
210 1
0.1%
193 1
0.1%
188 1
0.1%
167 1
0.1%
164 1
0.1%
156 1
0.1%
153 1
0.1%

20-29세
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct31
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.566474
Minimum0
Maximum496
Zeros572
Zeros (%)41.3%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:32.360759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile7.85
Maximum496
Range496
Interquartile range (IQR)3

Descriptive statistics

Standard deviation13.990284
Coefficient of variation (CV)5.4511692
Kurtosis1121.6742
Mean2.566474
Median Absolute Deviation (MAD)1
Skewness31.99836
Sum3552
Variance195.72804
MonotonicityNot monotonic
2024-03-14T19:55:32.763972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 572
41.3%
1 245
17.7%
2 174
 
12.6%
3 112
 
8.1%
4 87
 
6.3%
5 57
 
4.1%
6 45
 
3.3%
7 22
 
1.6%
8 14
 
1.0%
10 12
 
0.9%
Other values (21) 44
 
3.2%
ValueCountFrequency (%)
0 572
41.3%
1 245
17.7%
2 174
 
12.6%
3 112
 
8.1%
4 87
 
6.3%
5 57
 
4.1%
6 45
 
3.3%
7 22
 
1.6%
8 14
 
1.0%
9 7
 
0.5%
ValueCountFrequency (%)
496 1
0.1%
80 1
0.1%
47 1
0.1%
38 2
0.1%
37 2
0.1%
34 1
0.1%
27 1
0.1%
26 1
0.1%
25 1
0.1%
24 2
0.1%

30-39세
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct55
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8605491
Minimum0
Maximum566
Zeros339
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:32.994753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q38
95-th percentile20
Maximum566
Range566
Interquartile range (IQR)7

Descriptive statistics

Standard deviation17.898163
Coefficient of variation (CV)2.6088528
Kurtosis692.71957
Mean6.8605491
Median Absolute Deviation (MAD)4
Skewness22.885424
Sum9495
Variance320.34424
MonotonicityNot monotonic
2024-03-14T19:55:33.280992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 339
24.5%
3 102
 
7.4%
4 99
 
7.2%
5 98
 
7.1%
1 96
 
6.9%
2 93
 
6.7%
7 81
 
5.9%
6 80
 
5.8%
8 67
 
4.8%
10 39
 
2.8%
Other values (45) 290
21.0%
ValueCountFrequency (%)
0 339
24.5%
1 96
 
6.9%
2 93
 
6.7%
3 102
 
7.4%
4 99
 
7.2%
5 98
 
7.1%
6 80
 
5.8%
7 81
 
5.9%
8 67
 
4.8%
9 37
 
2.7%
ValueCountFrequency (%)
566 1
0.1%
123 1
0.1%
122 1
0.1%
106 1
0.1%
75 1
0.1%
74 1
0.1%
69 1
0.1%
64 1
0.1%
53 1
0.1%
52 1
0.1%

40-49세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct107
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.885116
Minimum0
Maximum682
Zeros264
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:33.690388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q317
95-th percentile50.85
Maximum682
Range682
Interquartile range (IQR)15

Descriptive statistics

Standard deviation31.200269
Coefficient of variation (CV)1.9641197
Kurtosis160.95401
Mean15.885116
Median Absolute Deviation (MAD)7
Skewness9.4097571
Sum21985
Variance973.45678
MonotonicityNot monotonic
2024-03-14T19:55:34.125083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 264
19.1%
10 72
 
5.2%
5 66
 
4.8%
6 64
 
4.6%
8 62
 
4.5%
9 62
 
4.5%
7 58
 
4.2%
4 58
 
4.2%
1 56
 
4.0%
3 53
 
3.8%
Other values (97) 569
41.1%
ValueCountFrequency (%)
0 264
19.1%
1 56
 
4.0%
2 34
 
2.5%
3 53
 
3.8%
4 58
 
4.2%
5 66
 
4.8%
6 64
 
4.6%
7 58
 
4.2%
8 62
 
4.5%
9 62
 
4.5%
ValueCountFrequency (%)
682 1
0.1%
290 1
0.1%
241 1
0.1%
216 1
0.1%
180 1
0.1%
174 1
0.1%
170 1
0.1%
160 1
0.1%
158 1
0.1%
157 1
0.1%

50-59세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct98
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.474711
Minimum0
Maximum1075
Zeros254
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:34.573821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q310
95-th percentile47.85
Maximum1075
Range1075
Interquartile range (IQR)8

Descriptive statistics

Standard deviation40.84267
Coefficient of variation (CV)3.2740374
Kurtosis360.64139
Mean12.474711
Median Absolute Deviation (MAD)4
Skewness15.873239
Sum17265
Variance1668.1237
MonotonicityNot monotonic
2024-03-14T19:55:34.827901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 254
18.4%
4 132
 
9.5%
3 107
 
7.7%
5 103
 
7.4%
7 92
 
6.6%
6 86
 
6.2%
2 80
 
5.8%
8 78
 
5.6%
9 65
 
4.7%
10 52
 
3.8%
Other values (88) 335
24.2%
ValueCountFrequency (%)
0 254
18.4%
1 29
 
2.1%
2 80
 
5.8%
3 107
7.7%
4 132
9.5%
5 103
7.4%
6 86
 
6.2%
7 92
 
6.6%
8 78
 
5.6%
9 65
 
4.7%
ValueCountFrequency (%)
1075 1
0.1%
566 1
0.1%
318 1
0.1%
263 1
0.1%
235 1
0.1%
218 1
0.1%
188 1
0.1%
180 1
0.1%
179 1
0.1%
178 1
0.1%

60-69세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct87
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.375
Minimum0
Maximum1087
Zeros415
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:35.082477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile27.85
Maximum1087
Range1087
Interquartile range (IQR)4

Descriptive statistics

Standard deviation44.299679
Coefficient of variation (CV)4.7252991
Kurtosis285.19141
Mean9.375
Median Absolute Deviation (MAD)2
Skewness14.260985
Sum12975
Variance1962.4616
MonotonicityNot monotonic
2024-03-14T19:55:35.336189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 415
30.0%
1 210
15.2%
2 185
13.4%
3 134
 
9.7%
4 99
 
7.2%
5 68
 
4.9%
6 42
 
3.0%
7 32
 
2.3%
8 23
 
1.7%
9 16
 
1.2%
Other values (77) 160
 
11.6%
ValueCountFrequency (%)
0 415
30.0%
1 210
15.2%
2 185
13.4%
3 134
 
9.7%
4 99
 
7.2%
5 68
 
4.9%
6 42
 
3.0%
7 32
 
2.3%
8 23
 
1.7%
9 16
 
1.2%
ValueCountFrequency (%)
1087 1
0.1%
564 1
0.1%
419 1
0.1%
342 1
0.1%
321 1
0.1%
313 1
0.1%
297 1
0.1%
274 1
0.1%
238 1
0.1%
229 1
0.1%

70-79세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8793353
Minimum0
Maximum1039
Zeros997
Zeros (%)72.0%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:35.597823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile18
Maximum1039
Range1039
Interquartile range (IQR)1

Descriptive statistics

Standard deviation41.965355
Coefficient of variation (CV)7.137772
Kurtosis316.43845
Mean5.8793353
Median Absolute Deviation (MAD)0
Skewness15.495559
Sum8137
Variance1761.091
MonotonicityNot monotonic
2024-03-14T19:55:35.941418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 997
72.0%
1 186
 
13.4%
2 42
 
3.0%
3 22
 
1.6%
4 21
 
1.5%
18 7
 
0.5%
14 6
 
0.4%
24 6
 
0.4%
26 6
 
0.4%
15 6
 
0.4%
Other values (49) 85
 
6.1%
ValueCountFrequency (%)
0 997
72.0%
1 186
 
13.4%
2 42
 
3.0%
3 22
 
1.6%
4 21
 
1.5%
5 4
 
0.3%
6 3
 
0.2%
7 2
 
0.1%
8 3
 
0.2%
9 2
 
0.1%
ValueCountFrequency (%)
1039 1
0.1%
645 1
0.1%
379 1
0.1%
318 1
0.1%
283 1
0.1%
259 1
0.1%
240 1
0.1%
238 2
0.1%
216 1
0.1%
206 1
0.1%

80-89세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83959538
Minimum0
Maximum151
Zeros1308
Zeros (%)94.5%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-03-14T19:55:36.160876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum151
Range151
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.5899232
Coefficient of variation (CV)9.0399774
Kurtosis203.84969
Mean0.83959538
Median Absolute Deviation (MAD)0
Skewness13.292068
Sum1162
Variance57.606934
MonotonicityNot monotonic
2024-03-14T19:55:36.565860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 1308
94.5%
2 22
 
1.6%
3 13
 
0.9%
1 8
 
0.6%
4 6
 
0.4%
5 3
 
0.2%
19 2
 
0.1%
61 2
 
0.1%
6 2
 
0.1%
12 1
 
0.1%
Other values (17) 17
 
1.2%
ValueCountFrequency (%)
0 1308
94.5%
1 8
 
0.6%
2 22
 
1.6%
3 13
 
0.9%
4 6
 
0.4%
5 3
 
0.2%
6 2
 
0.1%
7 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
151 1
0.1%
124 1
0.1%
92 1
0.1%
88 1
0.1%
72 1
0.1%
65 1
0.1%
61 2
0.1%
48 1
0.1%
43 1
0.1%
33 1
0.1%

90세 이상
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
0
1381 
8
 
1
1
 
1
15
 
1

Length

Max length2
Median length1
Mean length1.0007225
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1381
99.8%
8 1
 
0.1%
1 1
 
0.1%
15 1
 
0.1%

Length

2024-03-14T19:55:36.815932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:55:37.080939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1381
99.8%
8 1
 
0.1%
1 1
 
0.1%
15 1
 
0.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-14T19:55:37.232149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:37.392750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T19:55:22.836850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:01.145920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:03.920036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:06.474354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:09.005890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:11.567293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:14.204936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:16.364170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:18.967934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:21.105390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:22.996416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:01.390352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:04.167035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:06.717131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:09.254030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:11.815386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:14.464667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:16.513218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:19.229139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:21.256080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:23.165940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:01.642956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:04.419263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:06.967873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:09.506343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:12.132622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:14.729714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:16.732207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:19.482889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:21.459602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:23.324086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:01.895303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:04.666139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:07.210947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:09.756436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:12.392086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:14.985576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:16.979976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:19.729120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:21.644624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:23.486506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:02.166740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:04.921799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:07.465144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:10.008449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:12.634543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:15.250737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:17.235664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:19.983685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:21.797281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:23.651882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:02.419838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:05.176559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:07.720430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:10.263871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:12.891236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:15.514311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:17.666934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:20.239211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:21.954279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:23.915982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:02.692090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:05.444812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:07.984682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:10.529771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:13.162554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:15.694469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:17.939771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:20.464501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:22.121642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:24.079498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:02.946304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:05.697009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:08.233394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:10.793077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:13.421031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:15.856944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:18.192816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:20.626470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:22.276180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:24.241513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:03.199855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:05.951012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:08.486656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:11.034925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:13.678327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:16.022064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:18.445249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:20.781753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:22.427962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:24.404634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:03.450717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:06.206358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:08.743849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:11.295383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:13.932847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:16.184922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:18.696226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:20.938024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:55:22.618024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:55:37.541745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센터명강습요일시간장소정원대상구분0-9세10-19세20-29세30-39세40-49세50-59세60-69세70-79세80-89세90세 이상
센터명1.0000.3300.8110.7500.2210.8280.8490.2260.2990.0000.0000.1040.1570.0000.0510.0000.000
강습요일0.3301.0000.7350.8470.8140.7410.0000.0000.0000.2970.2630.2870.4830.4240.3380.4380.146
시간0.8110.7351.0000.6750.7790.9140.7250.5380.6160.0000.6570.7630.5350.7080.6100.6520.510
장소0.7500.8470.6751.0000.7400.8030.0000.1870.3870.4980.5350.5340.6060.4480.4360.4730.000
정원0.2210.8140.7790.7401.0000.3060.0000.0000.4840.8760.7910.7460.7960.8420.7930.8180.554
대상0.8280.7410.9140.8030.3061.0000.5210.6500.6990.0000.0000.1770.0000.0000.0000.0000.000
구분0.8490.0000.7250.0000.0000.5211.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
0-9세0.2260.0000.5380.1870.0000.6500.0001.0000.8220.0000.0000.0000.0000.0000.0000.0000.000
10-19세0.2990.0000.6160.3870.4840.6990.0000.8221.0000.7900.5700.5470.5370.5470.5470.6170.000
20-29세0.0000.2970.0000.4980.8760.0000.0000.0000.7901.0000.8030.9881.0001.0001.0001.0000.676
30-39세0.0000.2630.6570.5350.7910.0000.0000.0000.5700.8031.0000.8990.7810.8860.8510.8540.768
40-49세0.1040.2870.7630.5340.7460.1770.0000.0000.5470.9880.8991.0000.8180.9380.9080.8460.570
50-59세0.1570.4830.5350.6060.7960.0000.0000.0000.5371.0000.7810.8181.0000.8690.8310.8850.646
60-69세0.0000.4240.7080.4480.8420.0000.0000.0000.5471.0000.8860.9380.8691.0000.9870.9560.763
70-79세0.0510.3380.6100.4360.7930.0000.0000.0000.5471.0000.8510.9080.8310.9871.0000.9560.858
80-89세0.0000.4380.6520.4730.8180.0000.0000.0000.6171.0000.8540.8460.8850.9560.9561.0000.829
90세 이상0.0000.1460.5100.0000.5540.0000.0000.0000.0000.6760.7680.5700.6460.7630.8580.8291.000
2024-03-14T19:55:37.825377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상90세 이상시간강습요일센터명구분장소
대상1.0000.0000.6250.3120.4870.1830.367
90세 이상0.0001.0000.2850.0880.0000.0000.000
시간0.6250.2851.0000.3760.5390.3500.308
강습요일0.3120.0880.3761.0000.1430.0000.417
센터명0.4870.0000.5390.1431.0000.5130.407
구분0.1830.0000.3500.0000.5131.0000.000
장소0.3670.0000.3080.4170.4070.0001.000
2024-03-14T19:55:38.065825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원0-9세10-19세20-29세30-39세40-49세50-59세60-69세70-79세80-89세센터명강습요일시간장소대상구분90세 이상
정원1.000-0.202-0.168-0.0430.0440.1450.3640.4350.3390.4840.1430.5950.4760.4960.1600.0000.415
0-9세-0.2021.0000.698-0.475-0.594-0.635-0.637-0.554-0.274-0.1030.1320.0000.2310.0860.3650.0000.000
10-19세-0.1680.6981.000-0.156-0.259-0.306-0.367-0.484-0.299-0.1380.1780.0000.2800.1870.4110.0000.000
20-29세-0.043-0.475-0.1561.0000.6750.4930.4190.215-0.007-0.0890.0000.1860.0000.3440.0000.0000.706
30-39세0.044-0.594-0.2590.6751.0000.7490.5470.2750.024-0.1210.0000.1590.3990.3480.0000.0000.406
40-49세0.145-0.635-0.3060.4930.7491.0000.7210.3680.151-0.0180.0700.1550.4580.3160.0940.0000.404
50-59세0.364-0.637-0.3670.4190.5470.7211.0000.6000.3090.1590.0590.2200.2830.2950.0000.0000.575
60-69세0.435-0.554-0.4840.2150.2750.3680.6001.0000.5270.3810.0000.2380.4000.2550.0000.0000.603
70-79세0.339-0.274-0.299-0.0070.0240.1510.3090.5271.0000.4900.0340.1850.3180.2460.0000.0000.725
80-89세0.484-0.103-0.138-0.089-0.121-0.0180.1590.3810.4901.0000.0000.2160.3060.2370.0000.0000.704
센터명0.1430.1320.1780.0000.0000.0700.0590.0000.0340.0001.0000.1430.5390.4070.4870.5130.000
강습요일0.5950.0000.0000.1860.1590.1550.2200.2380.1850.2160.1431.0000.3760.4170.3120.0000.088
시간0.4760.2310.2800.0000.3990.4580.2830.4000.3180.3060.5390.3761.0000.3080.6250.3500.285
장소0.4960.0860.1870.3440.3480.3160.2950.2550.2460.2370.4070.4170.3081.0000.3670.0000.000
대상0.1600.3650.4110.0000.0000.0940.0000.0000.0000.0000.4870.3120.6250.3671.0000.1830.000
구분0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.5130.0000.3500.0000.1831.0000.000
90세 이상0.4150.0000.0000.7060.4060.4040.5750.6030.7250.7040.0000.0880.2850.0000.0000.0001.000

Missing values

2024-03-14T19:55:24.764962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:55:25.324043image/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

센터명프로그램명강습요일시간장소정원대상구분0-9세10-19세20-29세30-39세40-49세50-59세60-69세70-79세80-89세90세 이상데이터기준일
0동탄중앙어울림센터10시 그룹웨이트트레이닝A월수금10:00체력단련실10청소년/성인구분없음0022278120002023-12-31
1동탄중앙어울림센터10시 그룹웨이트트레이닝B화목10:00체력단련실10청소년/성인구분없음000837740002023-12-31
2동탄중앙어울림센터10시 서킷트레이닝A월수금10:00수영장15청소년/성인구분없음00003000002023-12-31
3동탄중앙어울림센터11시 그룹웨이트트레이닝A월수금11:00체력단련실10청소년/성인구분없음0052271500002023-12-31
4동탄중앙어울림센터14시 그룹웨이트트레이닝A월수금14:00체력단련실10성인/청소년구분없음00023651410002023-12-31
5동탄중앙어울림센터19시 그룹웨이트트레이닝B화목19:00체력단련실10청소년/성인구분없음00001000002023-12-31
6동탄중앙어울림센터7시 그룹웨이트트레이닝A월수금07:00체력단련실10성인/청소년구분없음011726421380002023-12-31
7동탄중앙어울림센터7시 그룹웨이트트레이닝B화목07:00체력단련실10성인/청소년구분없음031235500100002023-12-31
8동탄중앙어울림센터8시 그룹웨이트트레이닝A월수금08:00체력단련실10성인/청소년구분없음001184033110002023-12-31
9동탄중앙어울림센터9시 그룹웨이트트레이닝A월수금09:00체력단련실10청소년/성인구분없음003342700002023-12-31
센터명프로그램명강습요일시간장소정원대상구분0-9세10-19세20-29세30-39세40-49세50-59세60-69세70-79세80-89세90세 이상데이터기준일
1374화성그린환경센터성인 요가(B)-화목06시화목06:00~06:50G.X룸25성인/청소년구분없음010012550002023-12-31
1375화성그린환경센터성인 요가(B)-화목11시화목11:00~11:50G.X룸25성인/청소년구분없음00003000002023-12-31
1376화성그린환경센터어린이 음악줄넘기(월월수18:00~18:50G.X룸20어린이구분없음114000000002023-12-31
1377화성그린환경센터어린이 음악줄넘기(화화목18:00~18:50G.X룸20어린이구분없음114000000002023-12-31
1378화성그린환경센터바른자세 13시 (월수금)월수금13:00~13:50G.X룸25성인/청소년구분없음01015841002023-12-31
1379화성그린환경센터아이돌댄스월수금17:00~17:50G.X룸20어린이구분없음33000000002023-12-31
1380화성그린환경센터줌바(B) 19시 화목(성인)화목19:00~19:50G.X룸25성인구분없음000191200002023-12-31
1381화성그린환경센터줌바(C) 20시 화목(성인)화목20:00~20:50G.X룸25성인구분없음00016810002023-12-31
1382화성그린환경센터줌바(A) 10시 월수(성인)월수10:00~10:50G.X룸25성인구분없음000211320002023-12-31
1383화성그린환경센터신나는댄스월수금19:00~19:50G.X룸25성인구분없음000121410002023-12-31

Duplicate rows

Most frequently occurring

센터명프로그램명강습요일시간장소정원대상구분0-9세10-19세20-29세30-39세40-49세50-59세60-69세70-79세80-89세90세 이상데이터기준일# duplicates
7화성남부체육센터아쿠아로빅월수금11:00~11:50수영장50성인/청소년구분없음0000142624302023-12-314
8화성남부체육센터아쿠아로빅월수금11:00~11:50수영장50성인/청소년구분없음0000142626302023-12-314
2화성남부체육센터성인수영(오전)화목10:00~10:50수영장25성인/청소년상급반00001251002023-12-313
4화성남부체육센터성인수영(저녁)화목19:00~19:50수영장25성인/청소년상급반00143944002023-12-313
10화성남부체육센터어린이수영월수금16:00~16:50수영장25어린이중급반40000000002023-12-313
11화성남부체육센터어린이수영화목16:00~16:50수영장25어린이중급반59000000002023-12-313
0화성남부체육센터성인수영(새벽)화목07:00~07:50수영장25성인/청소년상급반00017711002023-12-312
1화성남부체육센터성인수영(새벽)화목07:00~07:50수영장25성인/청소년상급반00027510002023-12-312
3화성남부체육센터성인수영(저녁)월수금20:00~20:50수영장25성인/청소년중급반02643510002023-12-312
5화성남부체육센터성인수영(저녁)화목19:00~19:50수영장25성인/청소년중급반001431034002023-12-312