Overview

Dataset statistics

Number of variables14
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory129.6 B

Variable types

Categorical2
Numeric12

Dataset

Description2014-2019년 문예진흥기금 공모사업 중 문학 분야 "집필공간운영" 지원 사업의 공간가동내역(예: 공간가동일수, 자체 프로그램 수, 대관 프로그램 수 등)
Author한국문화예술위원회
URLhttps://www.data.go.kr/data/15076468/fileData.do

Alerts

공간가동일수(일) is highly overall correlated with 준비기간제외활용일수(일)High correlation
공간가동율(%) is highly overall correlated with 준비기간제외활용율(%)High correlation
준비기간제외활용일수(일) is highly overall correlated with 공간가동일수(일) and 2 other fieldsHigh correlation
준비기간제외활용율(%) is highly overall correlated with 공간가동율(%)High correlation
자체프로그램가동일수_금년(일) is highly overall correlated with 준비기간제외활용일수(일)High correlation
대관프로그램수_금년(건) is highly overall correlated with 대관프로그램가동일수_금년(일) and 1 other fieldsHigh correlation
대관프로그램가동일수_금년(일) is highly overall correlated with 대관프로그램수_금년(건) and 2 other fieldsHigh correlation
자체프로그램수_작년(건) is highly overall correlated with 자체프로그램가동일수_작년(일)High correlation
자체프로그램가동일수_작년(일) is highly overall correlated with 자체프로그램수_작년(건)High correlation
대관프로그램가동일수_작년(일) is highly overall correlated with 대관프로그램가동일수_금년(일)High correlation
문학단체명 is highly overall correlated with 준비기간제외활용일수(일)High correlation
대관프로그램수_작년(건) is highly overall correlated with 대관프로그램수_금년(건) and 1 other fieldsHigh correlation
대관프로그램수_작년(건) is highly imbalanced (63.2%)Imbalance
자체프로그램수_금년(건) has 1 (3.4%) zerosZeros
대관프로그램수_금년(건) has 19 (65.5%) zerosZeros
대관프로그램가동일수_금년(일) has 15 (51.7%) zerosZeros
자체프로그램수_작년(건) has 8 (27.6%) zerosZeros
자체프로그램가동일수_작년(일) has 7 (24.1%) zerosZeros
대관프로그램가동일수_작년(일) has 21 (72.4%) zerosZeros

Reproduction

Analysis started2023-12-12 09:04:10.903881
Analysis finished2023-12-12 09:04:29.483581
Duration18.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

문학단체명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
*을**집
*지**단
*1**학
*악**원
*날**날
Other values (2)

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row*악**원
2nd row*을**집
3rd row*1**학
4th row*지**단
5th row*날**날

Common Values

ValueCountFrequency (%)
*을**집 6
20.7%
*지**단 6
20.7%
*1**학 5
17.2%
*악**원 4
13.8%
*날**날 4
13.8%
*버**집 3
10.3%
*산**꽃 1
 
3.4%

Length

2023-12-12T18:04:29.577477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:29.751352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
을**집 6
20.7%
지**단 6
20.7%
1**학 5
17.2%
악**원 4
13.8%
날**날 4
13.8%
버**집 3
10.3%
산**꽃 1
 
3.4%

사업연도
Real number (ℝ)

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.4483
Minimum2014
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:29.916232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12015
median2016
Q32018
95-th percentile2019
Maximum2019
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.660168
Coefficient of variation (CV)0.00082331294
Kurtosis-1.1983475
Mean2016.4483
Median Absolute Deviation (MAD)1
Skewness0.072131122
Sum58477
Variance2.7561576
MonotonicityIncreasing
2023-12-12T18:04:30.078743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2015 6
20.7%
2016 5
17.2%
2017 5
17.2%
2018 5
17.2%
2014 4
13.8%
2019 4
13.8%
ValueCountFrequency (%)
2014 4
13.8%
2015 6
20.7%
2016 5
17.2%
2017 5
17.2%
2018 5
17.2%
2019 4
13.8%
ValueCountFrequency (%)
2019 4
13.8%
2018 5
17.2%
2017 5
17.2%
2016 5
17.2%
2015 6
20.7%
2014 4
13.8%

공간가동일수(일)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1490.0345
Minimum232
Maximum3550
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:30.235530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum232
5-th percentile324.4
Q1365
median1147
Q32798
95-th percentile3470.4
Maximum3550
Range3318
Interquartile range (IQR)2433

Descriptive statistics

Standard deviation1226.5028
Coefficient of variation (CV)0.82313717
Kurtosis-1.4584483
Mean1490.0345
Median Absolute Deviation (MAD)792
Skewness0.46748783
Sum43211
Variance1504309
MonotonicityNot monotonic
2023-12-12T18:04:30.402716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
365 9
31.0%
3490 1
 
3.4%
2160 1
 
3.4%
1455 1
 
3.4%
1260 1
 
3.4%
3101 1
 
3.4%
2825 1
 
3.4%
1089 1
 
3.4%
355 1
 
3.4%
2824 1
 
3.4%
Other values (11) 11
37.9%
ValueCountFrequency (%)
232 1
 
3.4%
306 1
 
3.4%
352 1
 
3.4%
355 1
 
3.4%
365 9
31.0%
1089 1
 
3.4%
1147 1
 
3.4%
1260 1
 
3.4%
1455 1
 
3.4%
1650 1
 
3.4%
ValueCountFrequency (%)
3550 1
3.4%
3490 1
3.4%
3441 1
3.4%
3192 1
3.4%
3101 1
3.4%
2825 1
3.4%
2824 1
3.4%
2798 1
3.4%
2527 1
3.4%
2172 1
3.4%

공간가동율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.52931
Minimum45
Maximum110.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:30.594548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile67.2
Q186
median91
Q398.08
95-th percentile101.88
Maximum110.7
Range65.7
Interquartile range (IQR)12.08

Descriptive statistics

Standard deviation13.146892
Coefficient of variation (CV)0.14684456
Kurtosis3.8076501
Mean89.52931
Median Absolute Deviation (MAD)7
Skewness-1.6483981
Sum2596.35
Variance172.84078
MonotonicityNot monotonic
2023-12-12T18:04:30.758984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
91.0 3
 
10.3%
92.0 2
 
6.9%
90.0 1
 
3.4%
75.0 1
 
3.4%
45.0 1
 
3.4%
84.0 1
 
3.4%
90.49 1
 
3.4%
96.0 1
 
3.4%
90.51 1
 
3.4%
76.0 1
 
3.4%
Other values (16) 16
55.2%
ValueCountFrequency (%)
45.0 1
3.4%
64.0 1
3.4%
72.0 1
3.4%
75.0 1
3.4%
76.0 1
3.4%
82.0 1
3.4%
84.0 1
3.4%
86.0 1
3.4%
90.0 1
3.4%
90.47 1
3.4%
ValueCountFrequency (%)
110.7 1
3.4%
102.0 1
3.4%
101.7 1
3.4%
100.0 1
3.4%
99.9 1
3.4%
98.7 1
3.4%
98.34 1
3.4%
98.08 1
3.4%
97.9 1
3.4%
96.0 1
3.4%

준비기간제외활용일수(일)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1526.1034
Minimum184
Maximum3320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:30.955006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184
5-th percentile279.4
Q1305
median1390
Q32693
95-th percentile3168
Maximum3320
Range3136
Interquartile range (IQR)2388

Descriptive statistics

Standard deviation1103.0465
Coefficient of variation (CV)0.72278622
Kurtosis-1.483548
Mean1526.1034
Median Absolute Deviation (MAD)1098
Skewness0.17130202
Sum44257
Variance1216711.7
MonotonicityNot monotonic
2023-12-12T18:04:31.142526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
280 3
 
10.3%
3190 1
 
3.4%
2716 1
 
3.4%
1350 1
 
3.4%
1172 1
 
3.4%
2989 1
 
3.4%
2083 1
 
3.4%
2717 1
 
3.4%
279 1
 
3.4%
306 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
184 1
 
3.4%
279 1
 
3.4%
280 3
10.3%
286 1
 
3.4%
292 1
 
3.4%
305 1
 
3.4%
306 1
 
3.4%
341 1
 
3.4%
1010 1
 
3.4%
1077 1
 
3.4%
ValueCountFrequency (%)
3320 1
3.4%
3190 1
3.4%
3135 1
3.4%
2989 1
3.4%
2810 1
3.4%
2717 1
3.4%
2716 1
3.4%
2693 1
3.4%
2114 1
3.4%
2101 1
3.4%

준비기간제외활용율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.198276
Minimum43
Maximum97.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:31.300041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile59.4
Q173.6
median80.6
Q382.7
95-th percentile93.96
Maximum97.2
Range54.2
Interquartile range (IQR)9.1

Descriptive statistics

Standard deviation11.454902
Coefficient of variation (CV)0.14838287
Kurtosis1.755351
Mean77.198276
Median Absolute Deviation (MAD)6.16
Skewness-0.89127009
Sum2238.75
Variance131.21477
MonotonicityNot monotonic
2023-12-12T18:04:31.419988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
74.44 3
 
10.3%
72.0 2
 
6.9%
81.0 2
 
6.9%
73.6 2
 
6.9%
64.0 2
 
6.9%
59.0 1
 
3.4%
43.0 1
 
3.4%
89.7 1
 
3.4%
96.0 1
 
3.4%
82.0 1
 
3.4%
Other values (13) 13
44.8%
ValueCountFrequency (%)
43.0 1
 
3.4%
59.0 1
 
3.4%
60.0 1
 
3.4%
64.0 2
6.9%
72.0 2
6.9%
73.6 2
6.9%
74.44 3
10.3%
76.7 1
 
3.4%
77.0 1
 
3.4%
80.6 1
 
3.4%
ValueCountFrequency (%)
97.2 1
3.4%
96.0 1
3.4%
90.9 1
3.4%
89.7 1
3.4%
85.8 1
3.4%
85.0 1
3.4%
83.0 1
3.4%
82.7 1
3.4%
82.23 1
3.4%
82.1 1
3.4%

자체프로그램수_금년(건)
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3103448
Minimum0
Maximum17
Zeros1
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:31.537757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile11.8
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.7235107
Coefficient of variation (CV)0.86385449
Kurtosis4.4895069
Mean4.3103448
Median Absolute Deviation (MAD)1
Skewness2.0290476
Sum125
Variance13.864532
MonotonicityNot monotonic
2023-12-12T18:04:31.676601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
3 7
24.1%
2 5
17.2%
4 5
17.2%
1 3
10.3%
6 2
 
6.9%
5 2
 
6.9%
0 1
 
3.4%
13 1
 
3.4%
9 1
 
3.4%
17 1
 
3.4%
ValueCountFrequency (%)
0 1
 
3.4%
1 3
10.3%
2 5
17.2%
3 7
24.1%
4 5
17.2%
5 2
 
6.9%
6 2
 
6.9%
9 1
 
3.4%
10 1
 
3.4%
13 1
 
3.4%
ValueCountFrequency (%)
17 1
 
3.4%
13 1
 
3.4%
10 1
 
3.4%
9 1
 
3.4%
6 2
 
6.9%
5 2
 
6.9%
4 5
17.2%
3 7
24.1%
2 5
17.2%
1 3
10.3%

자체프로그램가동일수_금년(일)
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32
Minimum2
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:31.861907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median18
Q342
95-th percentile107.2
Maximum193
Range191
Interquartile range (IQR)38

Descriptive statistics

Standard deviation41.649901
Coefficient of variation (CV)1.3015594
Kurtosis7.6783723
Mean32
Median Absolute Deviation (MAD)15
Skewness2.5490708
Sum928
Variance1734.7143
MonotonicityNot monotonic
2023-12-12T18:04:32.032475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2 3
 
10.3%
4 3
 
10.3%
24 2
 
6.9%
5 2
 
6.9%
15 2
 
6.9%
3 2
 
6.9%
42 2
 
6.9%
120 1
 
3.4%
16 1
 
3.4%
18 1
 
3.4%
Other values (10) 10
34.5%
ValueCountFrequency (%)
2 3
10.3%
3 2
6.9%
4 3
10.3%
5 2
6.9%
9 1
 
3.4%
15 2
6.9%
16 1
 
3.4%
18 1
 
3.4%
23 1
 
3.4%
24 2
6.9%
ValueCountFrequency (%)
193 1
3.4%
120 1
3.4%
88 1
3.4%
58 1
3.4%
54 1
3.4%
48 1
3.4%
45 1
3.4%
42 2
6.9%
33 1
3.4%
27 1
3.4%

대관프로그램수_금년(건)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.275862
Minimum0
Maximum365
Zeros19
Zeros (%)65.5%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:32.171540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4.6
Maximum365
Range365
Interquartile range (IQR)1

Descriptive statistics

Standard deviation67.658753
Coefficient of variation (CV)5.0963736
Kurtosis28.976003
Mean13.275862
Median Absolute Deviation (MAD)0
Skewness5.3819507
Sum385
Variance4577.7069
MonotonicityNot monotonic
2023-12-12T18:04:32.331591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 19
65.5%
1 4
 
13.8%
2 2
 
6.9%
5 1
 
3.4%
3 1
 
3.4%
365 1
 
3.4%
4 1
 
3.4%
ValueCountFrequency (%)
0 19
65.5%
1 4
 
13.8%
2 2
 
6.9%
3 1
 
3.4%
4 1
 
3.4%
5 1
 
3.4%
365 1
 
3.4%
ValueCountFrequency (%)
365 1
 
3.4%
5 1
 
3.4%
4 1
 
3.4%
3 1
 
3.4%
2 2
 
6.9%
1 4
 
13.8%
0 19
65.5%

대관프로그램가동일수_금년(일)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.068966
Minimum0
Maximum365
Zeros15
Zeros (%)51.7%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:32.471087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3150
95-th percentile365
Maximum365
Range365
Interquartile range (IQR)150

Descriptive statistics

Standard deviation149.57247
Coefficient of variation (CV)1.6606438
Kurtosis-0.47622941
Mean90.068966
Median Absolute Deviation (MAD)0
Skewness1.2036874
Sum2612
Variance22371.924
MonotonicityNot monotonic
2023-12-12T18:04:32.646824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 15
51.7%
365 4
 
13.8%
1 3
 
10.3%
307 1
 
3.4%
33 1
 
3.4%
8 1
 
3.4%
313 1
 
3.4%
2 1
 
3.4%
336 1
 
3.4%
150 1
 
3.4%
ValueCountFrequency (%)
0 15
51.7%
1 3
 
10.3%
2 1
 
3.4%
8 1
 
3.4%
33 1
 
3.4%
150 1
 
3.4%
307 1
 
3.4%
313 1
 
3.4%
336 1
 
3.4%
365 4
 
13.8%
ValueCountFrequency (%)
365 4
 
13.8%
336 1
 
3.4%
313 1
 
3.4%
307 1
 
3.4%
150 1
 
3.4%
33 1
 
3.4%
8 1
 
3.4%
2 1
 
3.4%
1 3
 
10.3%
0 15
51.7%

자체프로그램수_작년(건)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4827586
Minimum0
Maximum8
Zeros8
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:32.795069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile5.6
Maximum8
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.1317446
Coefficient of variation (CV)0.85861935
Kurtosis-0.059283589
Mean2.4827586
Median Absolute Deviation (MAD)2
Skewness0.57201588
Sum72
Variance4.544335
MonotonicityNot monotonic
2023-12-12T18:04:32.965156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 8
27.6%
3 5
17.2%
2 5
17.2%
4 4
13.8%
5 3
 
10.3%
1 2
 
6.9%
8 1
 
3.4%
6 1
 
3.4%
ValueCountFrequency (%)
0 8
27.6%
1 2
 
6.9%
2 5
17.2%
3 5
17.2%
4 4
13.8%
5 3
 
10.3%
6 1
 
3.4%
8 1
 
3.4%
ValueCountFrequency (%)
8 1
 
3.4%
6 1
 
3.4%
5 3
 
10.3%
4 4
13.8%
3 5
17.2%
2 5
17.2%
1 2
 
6.9%
0 8
27.6%

자체프로그램가동일수_작년(일)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.551724
Minimum0
Maximum313
Zeros7
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:33.173823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q342
95-th percentile95.2
Maximum313
Range313
Interquartile range (IQR)40

Descriptive statistics

Standard deviation60.957003
Coefficient of variation (CV)2.0627224
Kurtosis17.592131
Mean29.551724
Median Absolute Deviation (MAD)5
Skewness3.9349843
Sum857
Variance3715.7562
MonotonicityNot monotonic
2023-12-12T18:04:33.405824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 7
24.1%
3 3
 
10.3%
15 2
 
6.9%
4 2
 
6.9%
5 2
 
6.9%
120 1
 
3.4%
42 1
 
3.4%
48 1
 
3.4%
14 1
 
3.4%
16 1
 
3.4%
Other values (8) 8
27.6%
ValueCountFrequency (%)
0 7
24.1%
2 1
 
3.4%
3 3
10.3%
4 2
 
6.9%
5 2
 
6.9%
9 1
 
3.4%
14 1
 
3.4%
15 2
 
6.9%
16 1
 
3.4%
25 1
 
3.4%
ValueCountFrequency (%)
313 1
3.4%
120 1
3.4%
58 1
3.4%
56 1
3.4%
50 1
3.4%
48 1
3.4%
47 1
3.4%
42 1
3.4%
25 1
3.4%
16 1
3.4%

대관프로그램수_작년(건)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
0
25 
360
 
1
1
 
1
3
 
1
4
 
1

Length

Max length3
Median length1
Mean length1.0689655
Min length1

Unique

Unique4 ?
Unique (%)13.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 25
86.2%
360 1
 
3.4%
1 1
 
3.4%
3 1
 
3.4%
4 1
 
3.4%

Length

2023-12-12T18:04:33.599261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:04:33.775086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 25
86.2%
360 1
 
3.4%
1 1
 
3.4%
3 1
 
3.4%
4 1
 
3.4%

대관프로그램가동일수_작년(일)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.965517
Minimum0
Maximum365
Zeros21
Zeros (%)72.4%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T18:04:33.923876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile365
Maximum365
Range365
Interquartile range (IQR)1

Descriptive statistics

Standard deviation151.75885
Coefficient of variation (CV)1.8073949
Kurtosis-0.33341893
Mean83.965517
Median Absolute Deviation (MAD)0
Skewness1.2921418
Sum2435
Variance23030.749
MonotonicityNot monotonic
2023-12-12T18:04:34.064651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 21
72.4%
365 3
 
10.3%
336 2
 
6.9%
307 1
 
3.4%
360 1
 
3.4%
1 1
 
3.4%
ValueCountFrequency (%)
0 21
72.4%
1 1
 
3.4%
307 1
 
3.4%
336 2
 
6.9%
360 1
 
3.4%
365 3
 
10.3%
ValueCountFrequency (%)
365 3
 
10.3%
360 1
 
3.4%
336 2
 
6.9%
307 1
 
3.4%
1 1
 
3.4%
0 21
72.4%

Interactions

2023-12-12T18:04:27.224741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:11.401544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.706382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.300603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:15.889013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.279112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.688462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.119156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.425739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:22.860575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:24.236466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.790889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:27.423273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:11.490399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.856698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.410059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:15.971050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.398233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.786935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.218168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.521953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:22.961140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:24.467192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.888933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:27.567024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:11.583682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.981967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.529470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.052969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.496358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.901911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.312992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.614801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.052941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:24.579847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.015718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:27.677309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:11.679101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:13.148816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.642023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.142637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.612670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.040295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.443310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.705511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.152480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:24.687304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.127930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:27.787901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:11.761950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:13.262545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.758507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.234859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.705365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.174089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.545505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.785760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.250962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:24.782467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.226609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:27.892162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:11.865990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:13.380077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.843930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.335821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.805013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.281577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.648208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.867157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.346211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:24.933018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.331567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:28.041433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:11.992972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:13.501033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.972915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.423976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.939353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.395669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.783323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.991522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.451199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.067598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.464116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:28.144274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.115322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:13.635167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:15.107337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.527033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.062495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.557201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:20.918562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:22.092077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.573307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.178552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.614538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:28.228850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.213958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:13.765774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:15.218800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.643827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.192355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.684274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.017947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:22.171125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.684633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.275941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.743862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:28.331044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.319253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:13.897068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:15.308850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:16.847602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.312831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.785173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.124382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:22.559455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.798575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.397187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.867018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:28.437120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.428514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.046412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:15.411381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.001622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.434245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.891012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.230906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:22.661764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:23.922775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.542374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:26.983953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:28.541495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:12.541720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:14.155349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:15.504158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:17.139269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:18.554655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:19.999668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:21.330164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:22.760439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:24.079216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:25.680045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:04:27.084261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:04:34.163919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문학단체명사업연도공간가동일수(일)공간가동율(%)준비기간제외활용일수(일)준비기간제외활용율(%)자체프로그램수_금년(건)자체프로그램가동일수_금년(일)대관프로그램수_금년(건)대관프로그램가동일수_금년(일)자체프로그램수_작년(건)자체프로그램가동일수_작년(일)대관프로그램수_작년(건)대관프로그램가동일수_작년(일)
문학단체명1.0000.0000.7320.4350.7990.5770.7580.3850.0000.5160.0000.4120.0000.533
사업연도0.0001.0000.5310.1450.0000.0000.0000.3230.0730.0000.6470.0000.2340.000
공간가동일수(일)0.7320.5311.0000.6240.9020.2040.5570.0000.5220.0000.0000.0000.0000.683
공간가동율(%)0.4350.1450.6241.0000.6940.9510.0000.0000.0000.0000.1050.0000.0000.000
준비기간제외활용일수(일)0.7990.0000.9020.6941.0000.6180.0000.7830.0000.0000.0000.4580.0000.404
준비기간제외활용율(%)0.5770.0000.2040.9510.6181.0000.0000.2560.0000.0000.0000.0000.0000.000
자체프로그램수_금년(건)0.7580.0000.5570.0000.0000.0001.0000.0000.0000.5030.7330.6460.0000.433
자체프로그램가동일수_금년(일)0.3850.3230.0000.0000.7830.2560.0001.0000.0000.2860.2070.8220.0000.615
대관프로그램수_금년(건)0.0000.0730.5220.0000.0000.0000.0000.0001.0000.4100.0000.0001.0000.164
대관프로그램가동일수_금년(일)0.5160.0000.0000.0000.0000.0000.5030.2860.4101.0000.6090.7810.6730.784
자체프로그램수_작년(건)0.0000.6470.0000.1050.0000.0000.7330.2070.0000.6091.0000.8760.2450.000
자체프로그램가동일수_작년(일)0.4120.0000.0000.0000.4580.0000.6460.8220.0000.7810.8761.0000.0000.252
대관프로그램수_작년(건)0.0000.2340.0000.0000.0000.0000.0000.0001.0000.6730.2450.0001.0000.384
대관프로그램가동일수_작년(일)0.5330.0000.6830.0000.4040.0000.4330.6150.1640.7840.0000.2520.3841.000
2023-12-12T18:04:34.318856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대관프로그램수_작년(건)문학단체명
대관프로그램수_작년(건)1.0000.000
문학단체명0.0001.000
2023-12-12T18:04:34.424539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업연도공간가동일수(일)공간가동율(%)준비기간제외활용일수(일)준비기간제외활용율(%)자체프로그램수_금년(건)자체프로그램가동일수_금년(일)대관프로그램수_금년(건)대관프로그램가동일수_금년(일)자체프로그램수_작년(건)자체프로그램가동일수_작년(일)대관프로그램가동일수_작년(일)문학단체명대관프로그램수_작년(건)
사업연도1.000-0.157-0.447-0.174-0.296-0.058-0.204-0.0240.1380.3680.1670.2550.0000.000
공간가동일수(일)-0.1571.0000.2430.850-0.0580.2770.379-0.096-0.2630.0420.082-0.3060.4830.000
공간가동율(%)-0.4470.2431.0000.3320.654-0.0590.3290.0970.284-0.263-0.0550.2790.2230.000
준비기간제외활용일수(일)-0.1740.8500.3321.0000.0930.4250.593-0.062-0.0500.0930.182-0.1420.5800.000
준비기간제외활용율(%)-0.296-0.0580.6540.0931.000-0.0560.1790.0850.170-0.2590.0510.1220.3340.000
자체프로그램수_금년(건)-0.0580.277-0.0590.425-0.0561.0000.1660.024-0.2260.203-0.209-0.3730.3440.000
자체프로그램가동일수_금년(일)-0.2040.3790.3290.5930.1790.1661.000-0.2390.280-0.0370.4120.3960.2160.000
대관프로그램수_금년(건)-0.024-0.0960.097-0.0620.0850.024-0.2391.0000.5940.2150.0370.0960.0000.943
대관프로그램가동일수_금년(일)0.138-0.2630.284-0.0500.170-0.2260.2800.5941.0000.1760.4370.7250.3470.590
자체프로그램수_작년(건)0.3680.042-0.2630.093-0.2590.203-0.0370.2150.1761.0000.590-0.0040.0000.102
자체프로그램가동일수_작년(일)0.1670.082-0.0550.1820.051-0.2090.4120.0370.4370.5901.0000.3620.2620.000
대관프로그램가동일수_작년(일)0.255-0.3060.279-0.1420.122-0.3730.3960.0960.725-0.0040.3621.0000.3780.295
문학단체명0.0000.4830.2230.5800.3340.3440.2160.0000.3470.0000.2620.3781.0000.000
대관프로그램수_작년(건)0.0000.0000.0000.0000.0000.0000.0000.9430.5900.1020.0000.2950.0001.000

Missing values

2023-12-12T18:04:28.756143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:04:29.366412image/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

문학단체명사업연도공간가동일수(일)공간가동율(%)준비기간제외활용일수(일)준비기간제외활용율(%)자체프로그램수_금년(건)자체프로그램가동일수_금년(일)대관프로그램수_금년(건)대관프로그램가동일수_금년(일)자체프로그램수_작년(건)자체프로그램가동일수_작년(일)대관프로그램수_작년(건)대관프로그램가동일수_작년(일)
0*악**원2014349090.0319072.0312000312000
1*을**집2014217298.34208281.305803070580307
2*1**학2014365102.029282.122113300
3*지**단20143192101.7313585.86270055600
4*날**날201523282.018481.01324000000
5*악**원2015355095.0281077.0654000000
6*산**꽃201530692.0139097.235000000
7*을**집2015252798.7211482.7445000000
8*1**학201536591.028073.623000000
9*지**단20153441110.7332090.95335330000
문학단체명사업연도공간가동일수(일)공간가동율(%)준비기간제외활용일수(일)준비기간제외활용율(%)자체프로그램수_금년(건)자체프로그램가동일수_금년(일)대관프로그램수_금년(건)대관프로그램가동일수_금년(일)자체프로그램수_작년(건)자체프로그램가동일수_작년(일)대관프로그램수_작년(건)대관프로그램가동일수_작년(일)
19*을**집201736595.56184072.0319303653420365
20*버**집2018108972.0101060.054004400
21*날**날2018365100.028685.0342150354336
22*을**집201836597.930682.024803653470365
23*1**학201836576.027996.0120011600
24*지**단2018282590.51271774.444150041400
25*을**집201936596.0208389.738803652480365
26*지**단2019310190.49298974.444181141500
27*버**집2019126084.0117264.044005400
28*악**원2019145545.0135043.02150021500