Overview

Dataset statistics

Number of variables32
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory282.2 B

Variable types

Text2
Numeric13
Categorical17

Dataset

Description서울특별시_동대문구_실외운동기구현황(체육시설명, 시설주소, 운동기구유형, 운동기구 관리횟수, 고장난 실외운동기구, 고장난 실외운동기구 수량, 관리부서, 데이터기준일자 등)
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15038329/fileData.do

Alerts

스쿼트머신 유형 has constant value ""Constant
운동기구 관리횟수 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
어깨근육풀기 유형 is highly imbalanced (64.6%)Imbalance
역기내리기 유형 is highly imbalanced (60.3%)Imbalance
거꾸로매달리기 유형 is highly imbalanced (53.3%)Imbalance
철봉 유형 is highly imbalanced (60.7%)Imbalance
좌식싸이클 유형 is highly imbalanced (87.8%)Imbalance
기타유형 종류 is highly imbalanced (62.8%)Imbalance
고장난 실외운동기구 is highly imbalanced (87.8%)Imbalance
고장난 실외운동기구 수량 is highly imbalanced (87.8%)Imbalance
체육시설명 has unique valuesUnique
시설주소 has unique valuesUnique
공중걷기 유형 has 10 (16.7%) zerosZeros
파도타기 유형 has 19 (31.7%) zerosZeros
허리돌리기 유형 has 20 (33.3%) zerosZeros
상체근육풀기 유형 has 21 (35.0%) zerosZeros
역기올리기 유형 has 39 (65.0%) zerosZeros
레그프레스 유형 has 43 (71.7%) zerosZeros
윗몸일으키기 유형 has 43 (71.7%) zerosZeros
등허리지압기 유형 has 45 (75.0%) zerosZeros
하체근육풀기 유형 has 54 (90.0%) zerosZeros
평행봉 유형 has 53 (88.3%) zerosZeros
기타유형 has 49 (81.7%) zerosZeros

Reproduction

Analysis started2024-04-21 01:06:58.310324
Analysis finished2024-04-21 01:06:58.912633
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

체육시설명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-21T10:06:59.061562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length9.5833333
Min length5

Characters and Unicode

Total characters575
Distinct characters126
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row배봉산근린공원
2nd row답십리근린공원
3rd row홍릉근린공원
4th row장평근린공원
5th row장안근린공원
ValueCountFrequency (%)
정릉천 9
 
8.5%
마을마당 6
 
5.7%
성북천 4
 
3.8%
하부 4
 
3.8%
자전거도로 3
 
2.8%
산책로 3
 
2.8%
용두4교~용두1교 3
 
2.8%
용두교 3
 
2.8%
제기1교 2
 
1.9%
둔치 2
 
1.9%
Other values (66) 67
63.2%
2024-04-21T10:06:59.361192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
 
8.2%
원 40
 
7.0%
공 39
 
6.8%
린 32
 
5.6%
이 25
 
4.3%
어 24
 
4.2%
마 18
 
3.1%
교 17
 
3.0%
용 16
 
2.8%
천 15
 
2.6%
Other values (116) 302
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
88.2%
Space Separator 47
 
8.2%
Decimal Number 12
 
2.1%
Open Punctuation 3
 
0.5%
Math Symbol 3
 
0.5%
Close Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 40
 
7.9%
공 39
 
7.7%
린 32
 
6.3%
이 25
 
4.9%
어 24
 
4.7%
마 18
 
3.6%
교 17
 
3.4%
용 16
 
3.2%
천 15
 
3.0%
두 14
 
2.8%
Other values (109) 267
52.7%
Decimal Number
ValueCountFrequency (%)
1 7
58.3%
4 4
33.3%
5 1
 
8.3%
Space Separator
ValueCountFrequency (%)
47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
88.2%
Common 68
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 40
 
7.9%
공 39
 
7.7%
린 32
 
6.3%
이 25
 
4.9%
어 24
 
4.7%
마 18
 
3.6%
교 17
 
3.4%
용 16
 
3.2%
천 15
 
3.0%
두 14
 
2.8%
Other values (109) 267
52.7%
Common
ValueCountFrequency (%)
47
69.1%
1 7
 
10.3%
4 4
 
5.9%
( 3
 
4.4%
~ 3
 
4.4%
) 3
 
4.4%
5 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
88.2%
ASCII 68
 
11.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
69.1%
1 7
 
10.3%
4 4
 
5.9%
( 3
 
4.4%
~ 3
 
4.4%
) 3
 
4.4%
5 1
 
1.5%
Hangul
ValueCountFrequency (%)
원 40
 
7.9%
공 39
 
7.7%
린 32
 
6.3%
이 25
 
4.9%
어 24
 
4.7%
마 18
 
3.6%
교 17
 
3.4%
용 16
 
3.2%
천 15
 
3.0%
두 14
 
2.8%
Other values (109) 267
52.7%

시설주소
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-21T10:06:59.584777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length22.416667
Min length18

Characters and Unicode

Total characters1345
Distinct characters88
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row서울특별시 동대문구 전농동 산32-20
2nd row서울특별시 동대문구 답십리동 산2-9
3rd row서울특별시 동대문구 청량리동 산1-145
4th row서울특별시 동대문구 장안동 356
5th row서울특별시 동대문구 장안동 300
ValueCountFrequency (%)
서울특별시 60
22.4%
동대문구 60
22.4%
장안동 14
 
5.2%
정릉천 9
 
3.4%
휘경동 8
 
3.0%
답십리동 7
 
2.6%
전농동 7
 
2.6%
성북천 4
 
1.5%
이문동 3
 
1.1%
용두4교~용두1교 3
 
1.1%
Other values (80) 93
34.7%
2024-04-21T10:06:59.897819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
209
 
15.5%
동 107
 
8.0%
대 64
 
4.8%
문 63
 
4.7%
구 61
 
4.5%
서 60
 
4.5%
특 60
 
4.5%
별 60
 
4.5%
시 60
 
4.5%
울 60
 
4.5%
Other values (78) 541
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 888
66.0%
Space Separator 209
 
15.5%
Decimal Number 198
 
14.7%
Dash Punctuation 37
 
2.8%
Math Symbol 5
 
0.4%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 107
 
12.0%
대 64
 
7.2%
문 63
 
7.1%
구 61
 
6.9%
서 60
 
6.8%
특 60
 
6.8%
별 60
 
6.8%
시 60
 
6.8%
울 60
 
6.8%
교 17
 
1.9%
Other values (63) 276
31.1%
Decimal Number
ValueCountFrequency (%)
1 43
21.7%
3 24
12.1%
2 23
11.6%
4 21
10.6%
9 19
9.6%
5 18
9.1%
0 16
 
8.1%
6 13
 
6.6%
8 12
 
6.1%
7 9
 
4.5%
Space Separator
ValueCountFrequency (%)
209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 888
66.0%
Common 457
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 107
 
12.0%
대 64
 
7.2%
문 63
 
7.1%
구 61
 
6.9%
서 60
 
6.8%
특 60
 
6.8%
별 60
 
6.8%
시 60
 
6.8%
울 60
 
6.8%
교 17
 
1.9%
Other values (63) 276
31.1%
Common
ValueCountFrequency (%)
209
45.7%
1 43
 
9.4%
- 37
 
8.1%
3 24
 
5.3%
2 23
 
5.0%
4 21
 
4.6%
9 19
 
4.2%
5 18
 
3.9%
0 16
 
3.5%
6 13
 
2.8%
Other values (5) 34
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 888
66.0%
ASCII 457
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
209
45.7%
1 43
 
9.4%
- 37
 
8.1%
3 24
 
5.3%
2 23
 
5.0%
4 21
 
4.6%
9 19
 
4.2%
5 18
 
3.9%
0 16
 
3.5%
6 13
 
2.8%
Other values (5) 34
 
7.4%
Hangul
ValueCountFrequency (%)
동 107
 
12.0%
대 64
 
7.2%
문 63
 
7.1%
구 61
 
6.9%
서 60
 
6.8%
특 60
 
6.8%
별 60
 
6.8%
시 60
 
6.8%
울 60
 
6.8%
교 17
 
1.9%
Other values (63) 276
31.1%

위도
Real number (ℝ)

Distinct54
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.579038
Minimum37.563858
Maximum37.6038
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:00.021581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.563858
5-th percentile37.566822
Q137.571056
median37.577581
Q337.586363
95-th percentile37.594334
Maximum37.6038
Range0.0399416
Interquartile range (IQR)0.01530675

Descriptive statistics

Standard deviation0.0094420046
Coefficient of variation (CV)0.00025125722
Kurtosis-0.033676177
Mean37.579038
Median Absolute Deviation (MAD)0.0069545
Skewness0.65547209
Sum2254.7423
Variance8.9151451 × 10-5
MonotonicityNot monotonic
2024-04-21T10:07:00.140451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.570627 4
 
6.7%
37.58669 2
 
3.3%
37.5783 2
 
3.3%
37.57626 2
 
3.3%
37.58121369 1
 
1.7%
37.5809 1
 
1.7%
37.591079 1
 
1.7%
37.571164 1
 
1.7%
37.56962 1
 
1.7%
37.6038 1
 
1.7%
Other values (44) 44
73.3%
ValueCountFrequency (%)
37.5638584 1
1.7%
37.56484697 1
1.7%
37.56526436 1
1.7%
37.566904 1
1.7%
37.56748813 1
1.7%
37.56784857 1
1.7%
37.569038 1
1.7%
37.56962 1
1.7%
37.569659 1
1.7%
37.569871 1
1.7%
ValueCountFrequency (%)
37.6038 1
1.7%
37.60299 1
1.7%
37.59889444 1
1.7%
37.594094 1
1.7%
37.5935 1
1.7%
37.59228 1
1.7%
37.591079 1
1.7%
37.590018 1
1.7%
37.589274 1
1.7%
37.58812 1
1.7%

경도
Real number (ℝ)

Distinct54
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05331
Minimum127.02419
Maximum127.07888
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:00.280667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02419
5-th percentile127.02777
Q1127.03637
median127.05523
Q3127.06757
95-th percentile127.07172
Maximum127.07888
Range0.0546948
Interquartile range (IQR)0.031200575

Descriptive statistics

Standard deviation0.015768388
Coefficient of variation (CV)0.00012410844
Kurtosis-1.2313048
Mean127.05331
Median Absolute Deviation (MAD)0.01331635
Skewness-0.37123978
Sum7623.1989
Variance0.00024864207
MonotonicityNot monotonic
2024-04-21T10:07:00.416776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.070651 4
 
6.7%
127.03649 2
 
3.3%
127.03469 2
 
3.3%
127.03484 2
 
3.3%
127.0675923 1
 
1.7%
127.05447 1
 
1.7%
127.061154 1
 
1.7%
127.028504 1
 
1.7%
127.07888 1
 
1.7%
127.06756 1
 
1.7%
Other values (44) 44
73.3%
ValueCountFrequency (%)
127.0241852 1
1.7%
127.02664 1
1.7%
127.026725 1
1.7%
127.02782 1
1.7%
127.02808 1
1.7%
127.02809 1
1.7%
127.028504 1
1.7%
127.03469 2
3.3%
127.034812 1
1.7%
127.03483 1
1.7%
ValueCountFrequency (%)
127.07888 1
 
1.7%
127.0737398 1
 
1.7%
127.0725893 1
 
1.7%
127.071679 1
 
1.7%
127.07161 1
 
1.7%
127.0709026 1
 
1.7%
127.070651 4
6.7%
127.07054 1
 
1.7%
127.069106 1
 
1.7%
127.0679937 1
 
1.7%

공중걷기 유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3333333
Minimum0
Maximum14
Zeros10
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:00.504215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2.25
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1046089
Coefficient of variation (CV)1.5784567
Kurtosis24.368158
Mean1.3333333
Median Absolute Deviation (MAD)0
Skewness4.6766601
Sum80
Variance4.4293785
MonotonicityNot monotonic
2024-04-21T10:07:00.595050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 43
71.7%
0 10
 
16.7%
2 4
 
6.7%
8 1
 
1.7%
7 1
 
1.7%
14 1
 
1.7%
ValueCountFrequency (%)
0 10
 
16.7%
1 43
71.7%
2 4
 
6.7%
7 1
 
1.7%
8 1
 
1.7%
14 1
 
1.7%
ValueCountFrequency (%)
14 1
 
1.7%
8 1
 
1.7%
7 1
 
1.7%
2 4
 
6.7%
1 43
71.7%
0 10
 
16.7%

파도타기 유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1
Minimum0
Maximum15
Zeros19
Zeros (%)31.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:00.696558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2.15
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1288972
Coefficient of variation (CV)1.9353611
Kurtosis32.286425
Mean1.1
Median Absolute Deviation (MAD)0
Skewness5.3166726
Sum66
Variance4.5322034
MonotonicityNot monotonic
2024-04-21T10:07:00.775756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 37
61.7%
0 19
31.7%
5 1
 
1.7%
7 1
 
1.7%
2 1
 
1.7%
15 1
 
1.7%
ValueCountFrequency (%)
0 19
31.7%
1 37
61.7%
2 1
 
1.7%
5 1
 
1.7%
7 1
 
1.7%
15 1
 
1.7%
ValueCountFrequency (%)
15 1
 
1.7%
7 1
 
1.7%
5 1
 
1.7%
2 1
 
1.7%
1 37
61.7%
0 19
31.7%

허리돌리기 유형
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.85
Minimum0
Maximum27
Zeros20
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:00.861752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3.6
Maximum27
Range27
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.6242727
Coefficient of variation (CV)2.4996069
Kurtosis20.014477
Mean1.85
Median Absolute Deviation (MAD)1
Skewness4.4439895
Sum111
Variance21.383898
MonotonicityNot monotonic
2024-04-21T10:07:00.952843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 27
45.0%
0 20
33.3%
2 9
 
15.0%
27 1
 
1.7%
21 1
 
1.7%
15 1
 
1.7%
3 1
 
1.7%
ValueCountFrequency (%)
0 20
33.3%
1 27
45.0%
2 9
 
15.0%
3 1
 
1.7%
15 1
 
1.7%
21 1
 
1.7%
27 1
 
1.7%
ValueCountFrequency (%)
27 1
 
1.7%
21 1
 
1.7%
15 1
 
1.7%
3 1
 
1.7%
2 9
 
15.0%
1 27
45.0%
0 20
33.3%

상체근육풀기 유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.95
Minimum0
Maximum7
Zeros21
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:01.034925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3.05
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1992229
Coefficient of variation (CV)1.2623399
Kurtosis11.063905
Mean0.95
Median Absolute Deviation (MAD)0
Skewness2.8439261
Sum57
Variance1.4381356
MonotonicityNot monotonic
2024-04-21T10:07:01.125522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 32
53.3%
0 21
35.0%
4 2
 
3.3%
3 2
 
3.3%
2 2
 
3.3%
7 1
 
1.7%
ValueCountFrequency (%)
0 21
35.0%
1 32
53.3%
2 2
 
3.3%
3 2
 
3.3%
4 2
 
3.3%
7 1
 
1.7%
ValueCountFrequency (%)
7 1
 
1.7%
4 2
 
3.3%
3 2
 
3.3%
2 2
 
3.3%
1 32
53.3%
0 21
35.0%

달리기 유형
Categorical

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
33 
1
23 
2
 
2
8
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row8
2nd row4
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 33
55.0%
1 23
38.3%
2 2
 
3.3%
8 1
 
1.7%
4 1
 
1.7%

Length

2024-04-21T10:07:01.228593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:01.314244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 33
55.0%
1 23
38.3%
2 2
 
3.3%
8 1
 
1.7%
4 1
 
1.7%

역기올리기 유형
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0166667
Minimum0
Maximum15
Zeros39
Zeros (%)65.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:01.399645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5.05
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.6134701
Coefficient of variation (CV)2.5706263
Kurtosis18.44068
Mean1.0166667
Median Absolute Deviation (MAD)0
Skewness4.1360756
Sum61
Variance6.830226
MonotonicityNot monotonic
2024-04-21T10:07:01.490803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 39
65.0%
1 11
 
18.3%
2 6
 
10.0%
15 1
 
1.7%
12 1
 
1.7%
6 1
 
1.7%
5 1
 
1.7%
ValueCountFrequency (%)
0 39
65.0%
1 11
 
18.3%
2 6
 
10.0%
5 1
 
1.7%
6 1
 
1.7%
12 1
 
1.7%
15 1
 
1.7%
ValueCountFrequency (%)
15 1
 
1.7%
12 1
 
1.7%
6 1
 
1.7%
5 1
 
1.7%
2 6
 
10.0%
1 11
 
18.3%
0 39
65.0%

레그프레스 유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.51666667
Minimum0
Maximum8
Zeros43
Zeros (%)71.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:01.576322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2.05
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2553839
Coefficient of variation (CV)2.4297753
Kurtosis22.03393
Mean0.51666667
Median Absolute Deviation (MAD)0
Skewness4.2414543
Sum31
Variance1.5759887
MonotonicityNot monotonic
2024-04-21T10:07:01.665466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 43
71.7%
1 12
 
20.0%
2 2
 
3.3%
3 1
 
1.7%
4 1
 
1.7%
8 1
 
1.7%
ValueCountFrequency (%)
0 43
71.7%
1 12
 
20.0%
2 2
 
3.3%
3 1
 
1.7%
4 1
 
1.7%
8 1
 
1.7%
ValueCountFrequency (%)
8 1
 
1.7%
4 1
 
1.7%
3 1
 
1.7%
2 2
 
3.3%
1 12
 
20.0%
0 43
71.7%

어깨근육풀기 유형
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
54 
1
 
4
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 54
90.0%
1 4
 
6.7%
2 2
 
3.3%

Length

2024-04-21T10:07:01.762642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:01.847216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 54
90.0%
1 4
 
6.7%
2 2
 
3.3%

윗몸일으키기 유형
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2166667
Minimum0
Maximum25
Zeros43
Zeros (%)71.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:01.929449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3.4
Maximum25
Range25
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.2109287
Coefficient of variation (CV)3.4610373
Kurtosis22.457096
Mean1.2166667
Median Absolute Deviation (MAD)0
Skewness4.6828942
Sum73
Variance17.731921
MonotonicityNot monotonic
2024-04-21T10:07:02.013431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 43
71.7%
1 11
 
18.3%
2 2
 
3.3%
19 1
 
1.7%
11 1
 
1.7%
3 1
 
1.7%
25 1
 
1.7%
ValueCountFrequency (%)
0 43
71.7%
1 11
 
18.3%
2 2
 
3.3%
3 1
 
1.7%
11 1
 
1.7%
19 1
 
1.7%
25 1
 
1.7%
ValueCountFrequency (%)
25 1
 
1.7%
19 1
 
1.7%
11 1
 
1.7%
3 1
 
1.7%
2 2
 
3.3%
1 11
 
18.3%
0 43
71.7%

역기내리기 유형
Categorical

IMBALANCE 

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
49 
1
8 
6
 
1
9
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)5.0%

Sample

1st row6
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 49
81.7%
1 8
 
13.3%
6 1
 
1.7%
9 1
 
1.7%
2 1
 
1.7%

Length

2024-04-21T10:07:02.107009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:02.189490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 49
81.7%
1 8
 
13.3%
6 1
 
1.7%
9 1
 
1.7%
2 1
 
1.7%

등허리지압기 유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.55
Minimum0
Maximum9
Zeros45
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:02.268394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.25
95-th percentile2.05
Maximum9
Range9
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation1.5340762
Coefficient of variation (CV)2.7892295
Kurtosis20.145237
Mean0.55
Median Absolute Deviation (MAD)0
Skewness4.302516
Sum33
Variance2.3533898
MonotonicityNot monotonic
2024-04-21T10:07:02.352859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 45
75.0%
1 10
 
16.7%
2 2
 
3.3%
7 1
 
1.7%
3 1
 
1.7%
9 1
 
1.7%
ValueCountFrequency (%)
0 45
75.0%
1 10
 
16.7%
2 2
 
3.3%
3 1
 
1.7%
7 1
 
1.7%
9 1
 
1.7%
ValueCountFrequency (%)
9 1
 
1.7%
7 1
 
1.7%
3 1
 
1.7%
2 2
 
3.3%
1 10
 
16.7%
0 45
75.0%

노젓기 유형
Categorical

Distinct4
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
43 
1
14 
2
 
2
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row3
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 43
71.7%
1 14
 
23.3%
2 2
 
3.3%
3 1
 
1.7%

Length

2024-04-21T10:07:02.443048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:02.524507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
71.7%
1 14
 
23.3%
2 2
 
3.3%
3 1
 
1.7%

입식싸이클 유형
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
49 
1
9 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row3
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 49
81.7%
1 9
 
15.0%
3 2
 
3.3%

Length

2024-04-21T10:07:02.627092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:02.711256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 49
81.7%
1 9
 
15.0%
3 2
 
3.3%

거꾸로매달리기 유형
Categorical

IMBALANCE 

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
46 
1
10 
3
 
2
2
 
1
12
 
1

Length

Max length2
Median length1
Mean length1.0166667
Min length1

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row2
2nd row3
3rd row3
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 46
76.7%
1 10
 
16.7%
3 2
 
3.3%
2 1
 
1.7%
12 1
 
1.7%

Length

2024-04-21T10:07:02.796023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:02.896286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 46
76.7%
1 10
 
16.7%
3 2
 
3.3%
2 1
 
1.7%
12 1
 
1.7%

하체근육풀기 유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.43333333
Minimum0
Maximum10
Zeros54
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:02.972915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.15
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.69112
Coefficient of variation (CV)3.9025847
Kurtosis21.339853
Mean0.43333333
Median Absolute Deviation (MAD)0
Skewness4.5453139
Sum26
Variance2.859887
MonotonicityNot monotonic
2024-04-21T10:07:03.055334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 54
90.0%
1 2
 
3.3%
10 1
 
1.7%
5 1
 
1.7%
7 1
 
1.7%
2 1
 
1.7%
ValueCountFrequency (%)
0 54
90.0%
1 2
 
3.3%
2 1
 
1.7%
5 1
 
1.7%
7 1
 
1.7%
10 1
 
1.7%
ValueCountFrequency (%)
10 1
 
1.7%
7 1
 
1.7%
5 1
 
1.7%
2 1
 
1.7%
1 2
 
3.3%
0 54
90.0%

양팔줄당기기 유형
Categorical

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
42 
1
14 
2
 
2
4
 
1
8
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row4
2nd row2
3rd row0
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 42
70.0%
1 14
 
23.3%
2 2
 
3.3%
4 1
 
1.7%
8 1
 
1.7%

Length

2024-04-21T10:07:03.146263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:03.230926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42
70.0%
1 14
 
23.3%
2 2
 
3.3%
4 1
 
1.7%
8 1
 
1.7%

철봉 유형
Categorical

IMBALANCE 

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
50 
1
6 
6
 
2
3
 
1
8
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row6
2nd row6
3rd row1
4th row0
5th row3

Common Values

ValueCountFrequency (%)
0 50
83.3%
1 6
 
10.0%
6 2
 
3.3%
3 1
 
1.7%
8 1
 
1.7%

Length

2024-04-21T10:07:03.328394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:03.419457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 50
83.3%
1 6
 
10.0%
6 2
 
3.3%
3 1
 
1.7%
8 1
 
1.7%

평행봉 유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.63333333
Minimum0
Maximum13
Zeros53
Zeros (%)88.3%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:03.669942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.2
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4353795
Coefficient of variation (CV)3.8453361
Kurtosis19.118917
Mean0.63333333
Median Absolute Deviation (MAD)0
Skewness4.3916324
Sum38
Variance5.9310734
MonotonicityNot monotonic
2024-04-21T10:07:03.752876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 53
88.3%
1 3
 
5.0%
12 1
 
1.7%
7 1
 
1.7%
3 1
 
1.7%
13 1
 
1.7%
ValueCountFrequency (%)
0 53
88.3%
1 3
 
5.0%
3 1
 
1.7%
7 1
 
1.7%
12 1
 
1.7%
13 1
 
1.7%
ValueCountFrequency (%)
13 1
 
1.7%
12 1
 
1.7%
7 1
 
1.7%
3 1
 
1.7%
1 3
 
5.0%
0 53
88.3%

스쿼트머신 유형
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
60 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 60
100.0%

Length

2024-04-21T10:07:03.860723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:03.935004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 60
100.0%

좌식싸이클 유형
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
59 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 59
98.3%
1 1
 
1.7%

Length

2024-04-21T10:07:04.007971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:04.080280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 59
98.3%
1 1
 
1.7%

기타유형 종류
Categorical

IMBALANCE 

Distinct11
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
49 
몸통강화기
 
2
가슴모아주기 등
 
1
스트레칭기구 등
 
1
팔굽혀펴기 등
 
1
Other values (6)
6 

Length

Max length9
Median length1
Mean length1.9
Min length1

Unique

Unique9 ?
Unique (%)15.0%

Sample

1st row가슴모아주기 등
2nd row스트레칭기구 등
3rd row팔굽혀펴기 등
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 49
81.7%
몸통강화기 2
 
3.3%
가슴모아주기 등 1
 
1.7%
스트레칭기구 등 1
 
1.7%
팔굽혀펴기 등 1
 
1.7%
온몸뻗치기 1
 
1.7%
스텝퍼 1
 
1.7%
활차돌리기 1
 
1.7%
스텝퍼 외 1종 1
 
1.7%
지압로 외 2종 1
 
1.7%

Length

2024-04-21T10:07:04.169186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 49
73.1%
등 3
 
4.5%
몸통강화기 2
 
3.0%
스텝퍼 2
 
3.0%
외 2
 
3.0%
가슴모아주기 1
 
1.5%
스트레칭기구 1
 
1.5%
팔굽혀펴기 1
 
1.5%
온몸뻗치기 1
 
1.5%
활차돌리기 1
 
1.5%
Other values (4) 4
 
6.0%

기타유형
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93333333
Minimum0
Maximum23
Zeros49
Zeros (%)81.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-21T10:07:04.256520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.4
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5884309
Coefficient of variation (CV)3.8447474
Kurtosis26.84167
Mean0.93333333
Median Absolute Deviation (MAD)0
Skewness5.0125549
Sum56
Variance12.876836
MonotonicityNot monotonic
2024-04-21T10:07:04.339811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 49
81.7%
1 6
 
10.0%
2 2
 
3.3%
23 1
 
1.7%
13 1
 
1.7%
10 1
 
1.7%
ValueCountFrequency (%)
0 49
81.7%
1 6
 
10.0%
2 2
 
3.3%
10 1
 
1.7%
13 1
 
1.7%
23 1
 
1.7%
ValueCountFrequency (%)
23 1
 
1.7%
13 1
 
1.7%
10 1
 
1.7%
2 2
 
3.3%
1 6
 
10.0%
0 49
81.7%

운동기구 관리횟수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
수시
60 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수시 60
100.0%

Length

2024-04-21T10:07:04.432184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:04.506372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 60
100.0%

고장난 실외운동기구
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
59 
트위스트
 
1

Length

Max length4
Median length1
Mean length1.05
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 59
98.3%
트위스트 1
 
1.7%

Length

2024-04-21T10:07:04.594579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:04.691004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 59
98.3%
트위스트 1
 
1.7%

고장난 실외운동기구 수량
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
59 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 59
98.3%
1 1
 
1.7%

Length

2024-04-21T10:07:04.796481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:04.892393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 59
98.3%
1 1
 
1.7%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
서울특별시 동대문구
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 동대문구
2nd row서울특별시 동대문구
3rd row서울특별시 동대문구
4th row서울특별시 동대문구
5th row서울특별시 동대문구

Common Values

ValueCountFrequency (%)
서울특별시 동대문구 60
100.0%

Length

2024-04-21T10:07:04.981883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:05.058897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 60
50.0%
동대문구 60
50.0%

관리부서
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
정원도시과
46 
치수과
13 
문화체육과
 
1

Length

Max length6
Median length5
Mean length4.5833333
Min length3

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
정원도시과 46
76.7%
치수과 13
 
21.7%
문화체육과 1
 
1.7%

Length

2024-04-21T10:07:05.140324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:05.242449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정원도시과 46
76.7%
치수과 13
 
21.7%
문화체육과 1
 
1.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-27
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-27
2nd row2024-03-27
3rd row2024-03-27
4th row2024-03-27
5th row2024-03-27

Common Values

ValueCountFrequency (%)
2024-03-27 60
100.0%

Length

2024-04-21T10:07:05.349563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:07:05.448409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-27 60
100.0%

Sample

체육시설명시설주소위도경도공중걷기 유형파도타기 유형허리돌리기 유형상체근육풀기 유형달리기 유형역기올리기 유형레그프레스 유형어깨근육풀기 유형윗몸일으키기 유형역기내리기 유형등허리지압기 유형노젓기 유형입식싸이클 유형거꾸로매달리기 유형하체근육풀기 유형양팔줄당기기 유형철봉 유형평행봉 유형스쿼트머신 유형좌식싸이클 유형기타유형 종류기타유형운동기구 관리횟수고장난 실외운동기구고장난 실외운동기구 수량관리기관명관리부서데이터기준일자
0배봉산근린공원서울특별시 동대문구 전농동 산32-2037.581214127.0675928527481532196230210461200가슴모아주기 등23수시00서울특별시 동대문구정원도시과2024-03-27
1답십리근린공원서울특별시 동대문구 답십리동 산2-937.573094127.06382377214412401117113526700스트레칭기구 등13수시00서울특별시 동대문구정원도시과2024-03-27
2홍릉근린공원서울특별시 동대문구 청량리동 산1-14537.589274127.04320522212620311233001300팔굽혀펴기 등2수시00서울특별시 동대문구정원도시과2024-03-27
3장평근린공원서울특별시 동대문구 장안동 35637.567488127.073741123111011311002000000수시00서울특별시 동대문구정원도시과2024-03-27
4장안근린공원서울특별시 동대문구 장안동 30037.577165127.0709031111120010210100300000수시00서울특별시 동대문구정원도시과2024-03-27
5용두근린공원서울특별시 동대문구 용두동 34-137.573134127.0404611111120020101101000000수시00서울특별시 동대문구정원도시과2024-03-27
6텃골근린공원서울특별시 동대문구 전농동 690-137.577563127.0514270010100000110101000100수시00서울특별시 동대문구정원도시과2024-03-27
7새샘근린공원서울특별시 동대문구 답십리동 1004-37.569038127.0550261110100000000001000000수시00서울특별시 동대문구정원도시과2024-03-27
8천장어린이공원서울특별시 동대문구 이문동 264-18137.598894127.0538440110021000000000110000수시00서울특별시 동대문구정원도시과2024-03-27
9마로니에어린이공원서울특별시 동대문구 장안동 32537.570627127.0706510020000000000000000000수시00서울특별시 동대문구정원도시과2024-03-27
체육시설명시설주소위도경도공중걷기 유형파도타기 유형허리돌리기 유형상체근육풀기 유형달리기 유형역기올리기 유형레그프레스 유형어깨근육풀기 유형윗몸일으키기 유형역기내리기 유형등허리지압기 유형노젓기 유형입식싸이클 유형거꾸로매달리기 유형하체근육풀기 유형양팔줄당기기 유형철봉 유형평행봉 유형스쿼트머신 유형좌식싸이클 유형기타유형 종류기타유형운동기구 관리횟수고장난 실외운동기구고장난 실외운동기구 수량관리기관명관리부서데이터기준일자
50정릉천 용두1교 용두교 제방공원서울특별시 동대문구 정릉천 용두1교 용두교 제방공원37.5776127.034831111111000010000100000수시00서울특별시 동대문구치수과2024-03-27
51정릉천 용두교 하류 산책로서울특별시 동대문구 정릉천 용두교 하류 산책로37.5783127.034690111000000010000000000수시00서울특별시 동대문구치수과2024-03-27
52정릉천 용두교 하부 산책로서울특별시 동대문구 정릉천 용두교 하부 산책로37.5783127.034691000101000000000000000수시00서울특별시 동대문구치수과2024-03-27
53정릉천 복개주차장 하부 자전거도로서울특별시 동대문구 정릉천 복개주차장 하부 자전거도로37.58493127.0361111101000110000000000수시00서울특별시 동대문구치수과2024-03-27
54정릉천 제기1교 하부 자전거도로서울특별시 동대문구 정릉천 제기1교 하부 자전거도로37.58669127.036491120100010010000000000수시00서울특별시 동대문구치수과2024-03-27
55정릉천 제기1교 상류측(산책로)서울특별시 동대문구 정릉천 제기1교 상류측(산책로)37.58669127.036490001001000000000000000수시00서울특별시 동대문구치수과2024-03-27
56성북천 용미교 우안제방서울특별시 동대문구 성북천 용미교 우안제방37.57398127.028091111000010000000000000수시00서울특별시 동대문구치수과2024-03-27
57성북천 용신1교 하류측 좌안 제방서울특별시 동대문구 성북천 용신1교 하류측 좌안 제방37.5756127.0280811010001000000100000몸통강화기1수시00서울특별시 동대문구치수과2024-03-27
58성북천 용두초등학교 앞 둔치 산책로서울특별시 동대문구 성북천 용두초등학교 앞 둔치 산책로37.576155127.0278210111000000000100000몸통강화기1수시00서울특별시 동대문구치수과2024-03-27
59성북천 안감교 상류측 쌈지공원서울특별시 동대문구 성북천 안감교 상류측 쌈지공원37.57833127.026641111000010000000000000수시00서울특별시 동대문구치수과2024-03-27