Overview

Dataset statistics

Number of variables13
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory118.4 B

Variable types

Categorical1
Text1
Numeric11

Dataset

Description울산광역시의 관광 방문객 현황으로 각 구군의 관광지들의 연도별(2013~2023년) 방문객수 정보를 제공하고 있음.
Author울산광역시
URLhttps://www.data.go.kr/data/15052668/fileData.do

Alerts

2013년 is highly overall correlated with 2014년 and 2 other fieldsHigh correlation
2014년 is highly overall correlated with 2013년 and 2 other fieldsHigh correlation
2015년 is highly overall correlated with 2013년 and 2 other fieldsHigh correlation
2016년 is highly overall correlated with 2013년 and 2 other fieldsHigh correlation
2017년 is highly overall correlated with 2018년 and 2 other fieldsHigh correlation
2018년 is highly overall correlated with 2017년 and 5 other fieldsHigh correlation
2019년 is highly overall correlated with 2017년 and 5 other fieldsHigh correlation
2020년 is highly overall correlated with 2017년 and 5 other fieldsHigh correlation
2021년 is highly overall correlated with 2018년 and 4 other fieldsHigh correlation
2022년 is highly overall correlated with 2018년 and 4 other fieldsHigh correlation
2023년 is highly overall correlated with 2018년 and 4 other fieldsHigh correlation
구분 has unique valuesUnique
2019년 has unique valuesUnique
2020년 has unique valuesUnique
2021년 has unique valuesUnique
2022년 has unique valuesUnique
2023년 has unique valuesUnique
2013년 has 25 (65.8%) zerosZeros
2014년 has 24 (63.2%) zerosZeros
2015년 has 24 (63.2%) zerosZeros
2016년 has 20 (52.6%) zerosZeros
2017년 has 10 (26.3%) zerosZeros
2018년 has 2 (5.3%) zerosZeros
2021년 has 1 (2.6%) zerosZeros

Reproduction

Analysis started2024-03-14 14:27:22.934115
Analysis finished2024-03-14 14:27:53.580605
Duration30.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 군
Categorical

Distinct5
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size432.0 B
울주군
17 
동구
7 
남구
6 
중구
5 
북구
3 

Length

Max length5
Median length4
Mean length4.4473684
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울주군 17
44.7%
동구 7
18.4%
남구 6
 
15.8%
중구 5
 
13.2%
북구 3
 
7.9%

Length

2024-03-14T23:27:53.783151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:27:54.115731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울주군 17
44.7%
동구 7
18.4%
남구 6
 
15.8%
중구 5
 
13.2%
북구 3
 
7.9%

구분
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size432.0 B
2024-03-14T23:27:55.064992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.7105263
Min length2

Characters and Unicode

Total characters293
Distinct characters134
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row약사동제방유적전시관
2nd row외솔생가및기념관
3rd row울산동헌및내아
4th row태화강국가정원
5th row태화루
ValueCountFrequency (%)
약사동제방유적전시관 1
 
2.2%
국제클라이밍센터 1
 
2.2%
천전리 1
 
2.2%
각석 1
 
2.2%
반구대 1
 
2.2%
암각화 1
 
2.2%
번개맨 1
 
2.2%
우주센터 1
 
2.2%
석남사 1
 
2.2%
신불산 1
 
2.2%
Other values (35) 35
77.8%
2024-03-14T23:27:56.404854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 11
 
3.8%
관 10
 
3.4%
울 9
 
3.1%
7
 
2.4%
남 7
 
2.4%
대 7
 
2.4%
박 6
 
2.0%
원 6
 
2.0%
사 6
 
2.0%
공 6
 
2.0%
Other values (124) 218
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
90.8%
Lowercase Letter 9
 
3.1%
Space Separator 7
 
2.4%
Open Punctuation 5
 
1.7%
Close Punctuation 5
 
1.7%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 11
 
4.1%
관 10
 
3.8%
울 9
 
3.4%
남 7
 
2.6%
대 7
 
2.6%
박 6
 
2.3%
원 6
 
2.3%
사 6
 
2.3%
공 6
 
2.3%
물 6
 
2.3%
Other values (111) 192
72.2%
Lowercase Letter
ValueCountFrequency (%)
s 1
11.1%
p 1
11.1%
m 1
11.1%
o 1
11.1%
c 1
11.1%
k 1
11.1%
l 1
11.1%
e 1
11.1%
x 1
11.1%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
90.8%
Common 18
 
6.1%
Latin 9
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 11
 
4.1%
관 10
 
3.8%
울 9
 
3.4%
남 7
 
2.6%
대 7
 
2.6%
박 6
 
2.3%
원 6
 
2.3%
사 6
 
2.3%
공 6
 
2.3%
물 6
 
2.3%
Other values (111) 192
72.2%
Latin
ValueCountFrequency (%)
s 1
11.1%
p 1
11.1%
m 1
11.1%
o 1
11.1%
c 1
11.1%
k 1
11.1%
l 1
11.1%
e 1
11.1%
x 1
11.1%
Common
ValueCountFrequency (%)
7
38.9%
( 5
27.8%
) 5
27.8%
2 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
90.8%
ASCII 27
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 11
 
4.1%
관 10
 
3.8%
울 9
 
3.4%
남 7
 
2.6%
대 7
 
2.6%
박 6
 
2.3%
원 6
 
2.3%
사 6
 
2.3%
공 6
 
2.3%
물 6
 
2.3%
Other values (111) 192
72.2%
ASCII
ValueCountFrequency (%)
7
25.9%
( 5
18.5%
) 5
18.5%
s 1
 
3.7%
p 1
 
3.7%
m 1
 
3.7%
o 1
 
3.7%
c 1
 
3.7%
k 1
 
3.7%
l 1
 
3.7%
Other values (3) 3
11.1%

2013년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50234.263
Minimum0
Maximum362363
Zeros25
Zeros (%)65.8%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:27:56.762874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q346994.75
95-th percentile301682.7
Maximum362363
Range362363
Interquartile range (IQR)46994.75

Descriptive statistics

Standard deviation100236.22
Coefficient of variation (CV)1.9953755
Kurtosis4.144512
Mean50234.263
Median Absolute Deviation (MAD)0
Skewness2.2283257
Sum1908902
Variance1.0047299 × 1010
MonotonicityNot monotonic
2024-03-14T23:27:57.130348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 25
65.8%
11845 1
 
2.6%
362363 1
 
2.6%
291177 1
 
2.6%
225994 1
 
2.6%
36977 1
 
2.6%
151821 1
 
2.6%
103200 1
 
2.6%
138957 1
 
2.6%
361215 1
 
2.6%
Other values (4) 4
 
10.5%
ValueCountFrequency (%)
0 25
65.8%
11845 1
 
2.6%
25244 1
 
2.6%
36977 1
 
2.6%
50334 1
 
2.6%
51454 1
 
2.6%
98321 1
 
2.6%
103200 1
 
2.6%
138957 1
 
2.6%
151821 1
 
2.6%
ValueCountFrequency (%)
362363 1
2.6%
361215 1
2.6%
291177 1
2.6%
225994 1
2.6%
151821 1
2.6%
138957 1
2.6%
103200 1
2.6%
98321 1
2.6%
51454 1
2.6%
50334 1
2.6%

2014년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55133.868
Minimum0
Maximum498364
Zeros24
Zeros (%)63.2%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:27:57.684989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q344055.75
95-th percentile385744.75
Maximum498364
Range498364
Interquartile range (IQR)44055.75

Descriptive statistics

Standard deviation119922.22
Coefficient of variation (CV)2.1751099
Kurtosis7.2016118
Mean55133.868
Median Absolute Deviation (MAD)0
Skewness2.7736698
Sum2095087
Variance1.438134 × 1010
MonotonicityNot monotonic
2024-03-14T23:27:58.055455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 24
63.2%
9000 1
 
2.6%
498364 1
 
2.6%
379369 1
 
2.6%
144236 1
 
2.6%
40161 1
 
2.6%
113507 1
 
2.6%
62602 1
 
2.6%
107453 1
 
2.6%
116812 1
 
2.6%
Other values (5) 5
 
13.2%
ValueCountFrequency (%)
0 24
63.2%
9000 1
 
2.6%
29602 1
 
2.6%
32585 1
 
2.6%
40161 1
 
2.6%
45354 1
 
2.6%
62602 1
 
2.6%
94168 1
 
2.6%
107453 1
 
2.6%
113507 1
 
2.6%
ValueCountFrequency (%)
498364 1
2.6%
421874 1
2.6%
379369 1
2.6%
144236 1
2.6%
116812 1
2.6%
113507 1
2.6%
107453 1
2.6%
94168 1
2.6%
62602 1
2.6%
45354 1
2.6%

2015년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60052.342
Minimum0
Maximum595773
Zeros24
Zeros (%)63.2%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:27:58.393055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q347202.5
95-th percentile456683.7
Maximum595773
Range595773
Interquartile range (IQR)47202.5

Descriptive statistics

Standard deviation143405.59
Coefficient of variation (CV)2.38801
Kurtosis8.0830543
Mean60052.342
Median Absolute Deviation (MAD)0
Skewness2.962715
Sum2281989
Variance2.0565165 × 1010
MonotonicityNot monotonic
2024-03-14T23:27:58.748919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 24
63.2%
5060 1
 
2.6%
444894 1
 
2.6%
523492 1
 
2.6%
164864 1
 
2.6%
40001 1
 
2.6%
89598 1
 
2.6%
53668 1
 
2.6%
70521 1
 
2.6%
129601 1
 
2.6%
Other values (5) 5
 
13.2%
ValueCountFrequency (%)
0 24
63.2%
5060 1
 
2.6%
14622 1
 
2.6%
19791 1
 
2.6%
40001 1
 
2.6%
49603 1
 
2.6%
53668 1
 
2.6%
70521 1
 
2.6%
80501 1
 
2.6%
89598 1
 
2.6%
ValueCountFrequency (%)
595773 1
2.6%
523492 1
2.6%
444894 1
2.6%
164864 1
2.6%
129601 1
2.6%
89598 1
2.6%
80501 1
2.6%
70521 1
2.6%
53668 1
2.6%
49603 1
2.6%

2016년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64620.368
Minimum0
Maximum648295
Zeros20
Zeros (%)52.6%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:27:59.095480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q361508
95-th percentile359579.7
Maximum648295
Range648295
Interquartile range (IQR)61508

Descriptive statistics

Standard deviation137304.99
Coefficient of variation (CV)2.1247943
Kurtosis9.804287
Mean64620.368
Median Absolute Deviation (MAD)0
Skewness3.0559357
Sum2455574
Variance1.8852661 × 1010
MonotonicityNot monotonic
2024-03-14T23:27:59.471161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 20
52.6%
203561 1
 
2.6%
35775 1
 
2.6%
15624 1
 
2.6%
90456 1
 
2.6%
46049 1
 
2.6%
454948 1
 
2.6%
116780 1
 
2.6%
16354 1
 
2.6%
101039 1
 
2.6%
Other values (9) 9
23.7%
ValueCountFrequency (%)
0 20
52.6%
6081 1
 
2.6%
15624 1
 
2.6%
16354 1
 
2.6%
19708 1
 
2.6%
31005 1
 
2.6%
35775 1
 
2.6%
46009 1
 
2.6%
46049 1
 
2.6%
66661 1
 
2.6%
ValueCountFrequency (%)
648295 1
2.6%
454948 1
2.6%
342750 1
2.6%
203561 1
2.6%
146997 1
2.6%
116780 1
2.6%
101039 1
2.6%
90456 1
2.6%
67482 1
2.6%
66661 1
2.6%

2017년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128756.89
Minimum0
Maximum1062769
Zeros10
Zeros (%)26.3%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:27:59.860302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11180.25
median44799.5
Q3104922.75
95-th percentile637063.95
Maximum1062769
Range1062769
Interquartile range (IQR)103742.5

Descriptive statistics

Standard deviation232020.33
Coefficient of variation (CV)1.8020031
Kurtosis7.4355288
Mean128756.89
Median Absolute Deviation (MAD)44799.5
Skewness2.697696
Sum4892762
Variance5.3833432 × 1010
MonotonicityNot monotonic
2024-03-14T23:28:00.280795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 10
26.3%
45212 1
 
2.6%
41918 1
 
2.6%
13289 1
 
2.6%
85259 1
 
2.6%
56473 1
 
2.6%
520120 1
 
2.6%
99345 1
 
2.6%
5271 1
 
2.6%
62686 1
 
2.6%
Other values (19) 19
50.0%
ValueCountFrequency (%)
0 10
26.3%
4721 1
 
2.6%
5271 1
 
2.6%
13289 1
 
2.6%
19436 1
 
2.6%
20780 1
 
2.6%
26639 1
 
2.6%
41918 1
 
2.6%
43219 1
 
2.6%
44387 1
 
2.6%
ValueCountFrequency (%)
1062769 1
2.6%
723163 1
2.6%
621870 1
2.6%
520120 1
2.6%
347390 1
2.6%
212675 1
2.6%
207316 1
2.6%
174381 1
2.6%
110869 1
2.6%
106782 1
2.6%

2018년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean132382.08
Minimum0
Maximum905378
Zeros2
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:28:00.684059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3122.9
Q126205.75
median46840
Q3110034.25
95-th percentile600174.3
Maximum905378
Range905378
Interquartile range (IQR)83828.5

Descriptive statistics

Standard deviation204449.67
Coefficient of variation (CV)1.5443908
Kurtosis5.7796312
Mean132382.08
Median Absolute Deviation (MAD)38347
Skewness2.4604352
Sum5030519
Variance4.1799667 × 1010
MonotonicityNot monotonic
2024-03-14T23:28:01.077901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 2
 
5.3%
105010 1
 
2.6%
7289 1
 
2.6%
24837 1
 
2.6%
47496 1
 
2.6%
21332 1
 
2.6%
80895 1
 
2.6%
83983 1
 
2.6%
27978 1
 
2.6%
6717 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
0 2
5.3%
3674 1
2.6%
6717 1
2.6%
7062 1
2.6%
7289 1
2.6%
21332 1
2.6%
23463 1
2.6%
24837 1
2.6%
25742 1
2.6%
27597 1
2.6%
ValueCountFrequency (%)
905378 1
2.6%
615799 1
2.6%
597417 1
2.6%
556842 1
2.6%
363267 1
2.6%
189320 1
2.6%
179923 1
2.6%
173094 1
2.6%
171576 1
2.6%
111709 1
2.6%

2019년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136966.5
Minimum2627
Maximum826651
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:28:01.471677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2627
5-th percentile11474.6
Q130220.25
median57663.5
Q3167866
95-th percentile578429.85
Maximum826651
Range824024
Interquartile range (IQR)137645.75

Descriptive statistics

Standard deviation189709.54
Coefficient of variation (CV)1.3850798
Kurtosis5.0978421
Mean136966.5
Median Absolute Deviation (MAD)41520
Skewness2.3088964
Sum5204727
Variance3.5989709 × 1010
MonotonicityNot monotonic
2024-03-14T23:28:01.869906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
8707 1
 
2.6%
116209 1
 
2.6%
11963 1
 
2.6%
12533 1
 
2.6%
72867 1
 
2.6%
51131 1
 
2.6%
81400 1
 
2.6%
108944 1
 
2.6%
22913 1
 
2.6%
24147 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
2627 1
2.6%
8707 1
2.6%
11963 1
2.6%
12533 1
2.6%
14263 1
2.6%
17204 1
2.6%
18546 1
2.6%
22913 1
2.6%
24147 1
2.6%
29797 1
2.6%
ValueCountFrequency (%)
826651 1
2.6%
640921 1
2.6%
567402 1
2.6%
456243 1
2.6%
346978 1
2.6%
232688 1
2.6%
202358 1
2.6%
200104 1
2.6%
186046 1
2.6%
185085 1
2.6%

2020년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82023.684
Minimum461
Maximum616962
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:28:02.241042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum461
5-th percentile2987.2
Q117518.75
median38514
Q377504.75
95-th percentile255328.6
Maximum616962
Range616501
Interquartile range (IQR)59986

Descriptive statistics

Standard deviation120676.47
Coefficient of variation (CV)1.4712393
Kurtosis10.676057
Mean82023.684
Median Absolute Deviation (MAD)27133.5
Skewness3.0233841
Sum3116900
Variance1.456281 × 1010
MonotonicityNot monotonic
2024-03-14T23:28:02.647116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
3337 1
 
2.6%
160839 1
 
2.6%
6698 1
 
2.6%
11531 1
 
2.6%
56051 1
 
2.6%
18652 1
 
2.6%
75225 1
 
2.6%
77048 1
 
2.6%
28527 1
 
2.6%
23927 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
461 1
2.6%
1005 1
2.6%
3337 1
2.6%
3506 1
2.6%
6698 1
2.6%
11230 1
2.6%
11531 1
2.6%
12656 1
2.6%
16708 1
2.6%
17141 1
2.6%
ValueCountFrequency (%)
616962 1
2.6%
394528 1
2.6%
230764 1
2.6%
228730 1
2.6%
188847 1
2.6%
160839 1
2.6%
148801 1
2.6%
113478 1
2.6%
91904 1
2.6%
77657 1
2.6%

2021년
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92771.5
Minimum0
Maximum470189
Zeros1
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:28:03.040962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2449.7
Q119351
median42345
Q3145382.75
95-th percentile314914.1
Maximum470189
Range470189
Interquartile range (IQR)126031.75

Descriptive statistics

Standard deviation114167.23
Coefficient of variation (CV)1.2306282
Kurtosis4.1395659
Mean92771.5
Median Absolute Deviation (MAD)35170.5
Skewness2.0287026
Sum3525317
Variance1.3034156 × 1010
MonotonicityNot monotonic
2024-03-14T23:28:03.438541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
5848 1
 
2.6%
141401 1
 
2.6%
10088 1
 
2.6%
15806 1
 
2.6%
41693 1
 
2.6%
35512 1
 
2.6%
80320 1
 
2.6%
76614 1
 
2.6%
46033 1
 
2.6%
40198 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
0 1
2.6%
374 1
2.6%
2816 1
2.6%
5848 1
2.6%
6273 1
2.6%
10088 1
2.6%
13848 1
2.6%
15806 1
2.6%
17336 1
2.6%
18454 1
2.6%
ValueCountFrequency (%)
470189 1
2.6%
447577 1
2.6%
291503 1
2.6%
271371 1
2.6%
188525 1
2.6%
167606 1
2.6%
158476 1
2.6%
152089 1
2.6%
149087 1
2.6%
146710 1
2.6%

2022년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133960.95
Minimum1468
Maximum1008067
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:28:03.839426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1468
5-th percentile3390.05
Q128404.75
median62920.5
Q3131261.25
95-th percentile471956.7
Maximum1008067
Range1006599
Interquartile range (IQR)102856.5

Descriptive statistics

Standard deviation197249.75
Coefficient of variation (CV)1.4724422
Kurtosis10.129591
Mean133960.95
Median Absolute Deviation (MAD)46999
Skewness2.9242791
Sum5090516
Variance3.8907464 × 1010
MonotonicityNot monotonic
2024-03-14T23:28:04.277728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
6846 1
 
2.6%
71555 1
 
2.6%
12963 1
 
2.6%
21645 1
 
2.6%
54286 1
 
2.6%
48046 1
 
2.6%
95674 1
 
2.6%
125855 1
 
2.6%
44432 1
 
2.6%
32996 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
1468 1
2.6%
3141 1
2.6%
3434 1
2.6%
6846 1
2.6%
9919 1
2.6%
12963 1
2.6%
18880 1
2.6%
21645 1
2.6%
25355 1
2.6%
27475 1
2.6%
ValueCountFrequency (%)
1008067 1
2.6%
537507 1
2.6%
460389 1
2.6%
456869 1
2.6%
343540 1
2.6%
242627 1
2.6%
198336 1
2.6%
174831 1
2.6%
143286 1
2.6%
131271 1
2.6%

2023년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean247637.42
Minimum3045
Maximum5315836
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-14T23:28:04.680216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3045
5-th percentile7116.8
Q130941
median62210
Q3149343.5
95-th percentile436234.05
Maximum5315836
Range5312791
Interquartile range (IQR)118402.5

Descriptive statistics

Standard deviation852835.75
Coefficient of variation (CV)3.4438889
Kurtosis36.392327
Mean247637.42
Median Absolute Deviation (MAD)51396
Skewness5.9774745
Sum9410222
Variance7.2732882 × 1011
MonotonicityNot monotonic
2024-03-14T23:28:05.102120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
6039 1
 
2.6%
57662 1
 
2.6%
11780 1
 
2.6%
26912 1
 
2.6%
48223 1
 
2.6%
46084 1
 
2.6%
132227 1
 
2.6%
357385 1
 
2.6%
60952 1
 
2.6%
37931 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
3045 1
2.6%
6039 1
2.6%
7307 1
2.6%
9848 1
2.6%
11780 1
2.6%
12394 1
2.6%
15526 1
2.6%
18157 1
2.6%
26912 1
2.6%
30398 1
2.6%
ValueCountFrequency (%)
5315836 1
2.6%
436427 1
2.6%
436200 1
2.6%
357385 1
2.6%
335929 1
2.6%
327040 1
2.6%
212181 1
2.6%
187203 1
2.6%
166346 1
2.6%
155049 1
2.6%

Interactions

2024-03-14T23:27:50.039207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:23.565721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:26.306936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:29.014128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:31.301467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:33.997968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:36.664854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:39.275234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:41.880791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:44.763956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:47.362493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:50.291403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:23.823621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:26.560698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:29.169611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:31.554797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:34.255069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:36.917340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:39.526214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:42.135895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:45.012259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:47.618462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:50.532383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:24.076032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:26.795794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:29.309908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:31.796214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:34.497319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:37.149586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:39.760266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:42.564252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:45.245561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:47.858954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:50.776926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:24.328078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:27.040733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:29.457452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:32.042952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:34.744407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:37.390428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:40.004803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:42.824037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:45.485473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:48.108014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:51.029335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:24.582564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:27.283088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:29.605284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:32.296937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:34.989259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:37.628407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:40.244989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:43.068848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:45.722913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:48.353773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:51.269990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:24.832870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:27.529966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:29.835456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:32.543405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:35.230264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:37.868649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:40.486913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:43.314704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:45.960628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:48.598899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:51.500591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:25.075136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:27.762485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:30.070154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:32.783276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:35.460768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:38.096133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:40.715246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:43.547423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:46.186166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:48.832402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:51.734662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:25.317343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:27.993894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:30.308036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:33.018482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:35.704359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:38.323186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:40.939900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:43.783840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:46.417456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:49.067373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:51.978112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:25.570340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:28.240754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:30.554677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:33.268036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:35.949300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:38.566743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:41.180031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:44.035982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:46.656960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:49.313642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:52.215757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:25.807474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:28.469338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:30.792304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:33.504978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:36.181512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:38.793769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:41.405695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:44.271842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:46.885411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:49.549269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:52.456692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:26.057462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:28.874644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:31.054933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:33.752873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:36.423993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:39.034429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:41.646667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:44.517914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:47.123553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:27:49.791849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:28:05.399574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 군구분2013년2014년2015년2016년2017년2018년2019년2020년2021년2022년2023년
구 군1.0001.0000.0000.0000.0000.0000.3210.2570.5060.0000.0840.4920.229
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2013년0.0001.0001.0000.8770.9460.8740.9340.4320.8550.0000.8650.4470.000
2014년0.0001.0000.8771.0000.9930.9010.9060.8600.8750.6520.9040.7260.000
2015년0.0001.0000.9460.9931.0000.9400.9220.8660.8840.6240.9040.7320.000
2016년0.0001.0000.8740.9010.9401.0000.8480.6630.8930.7430.8590.7510.000
2017년0.3211.0000.9340.9060.9220.8481.0000.8900.9910.8910.9760.9191.000
2018년0.2571.0000.4320.8600.8660.6630.8901.0000.9250.9000.8740.8861.000
2019년0.5061.0000.8550.8750.8840.8930.9910.9251.0000.8840.9730.9301.000
2020년0.0001.0000.0000.6520.6240.7430.8910.9000.8841.0000.8150.8371.000
2021년0.0841.0000.8650.9040.9040.8590.9760.8740.9730.8151.0000.8710.783
2022년0.4921.0000.4470.7260.7320.7510.9190.8860.9300.8370.8711.0001.000
2023년0.2291.0000.0000.0000.0000.0001.0001.0001.0001.0000.7831.0001.000
2024-03-14T23:28:05.647583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2013년2014년2015년2016년2017년2018년2019년2020년2021년2022년2023년구 군
2013년1.0000.9540.9530.7690.4460.2280.161-0.0350.0110.0450.2140.000
2014년0.9541.0000.9990.7990.4690.2290.151-0.033-0.0100.0040.1490.000
2015년0.9530.9991.0000.8000.4690.2300.152-0.034-0.0110.0040.1470.000
2016년0.7690.7990.8001.0000.4440.2100.0840.0280.054-0.0250.0970.000
2017년0.4460.4690.4690.4441.0000.7410.6270.5620.4830.4140.4930.180
2018년0.2280.2290.2300.2100.7411.0000.9070.7350.6980.7060.7590.163
2019년0.1610.1510.1520.0840.6270.9071.0000.8450.8030.8400.8070.266
2020년-0.035-0.033-0.0340.0280.5620.7350.8451.0000.9290.8680.7430.000
2021년0.011-0.010-0.0110.0540.4830.6980.8030.9291.0000.9260.7590.000
2022년0.0450.0040.004-0.0250.4140.7060.8400.8680.9261.0000.8630.288
2023년0.2140.1490.1470.0970.4930.7590.8070.7430.7590.8631.0000.269
구 군0.0000.0000.0000.0000.1800.1630.2660.0000.0000.2880.2691.000

Missing values

2024-03-14T23:27:52.819416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:27:53.368812image/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

구 군구분2013년2014년2015년2016년2017년2018년2019년2020년2021년2022년2023년
0중구약사동제방유적전시관00000671787073337584868466039
1중구외솔생가및기념관000045212461845091829213285313119450075
2중구울산동헌및내아00004646042413488223681362733919969396
3중구태화강국가정원000010627699053788266516169624701895375075315836
4중구태화루000092140764321040296449442997360759848
5남구sk에너지울산complex118459000506020356147213674262746137414683045
6남구고래생태체험관362363498364444894342750347390363267346978113478188525343540335929
7남구울산대공원291177379369523492648295621870615799456243148801271371456869436200
8남구울산박물관2259941442361648646081212675171576186046402156521596285121284
9남구장생포고래문화마을0000011170923268854879146710242627327040
구 군구분2013년2014년2015년2016년2017년2018년2019년2020년2021년2022년2023년
28울주군영남알프스(배내고개)0001970819436279782291328527460334443260952
29울주군영남알프스(배내골 사슴목장)000101039626861050101162091608391414017155557662
30울주군영남알프스(석남사)000163545271257422414723927401983299637931
31울주군영남알프스(복합웰컴센터)00011678099345101168696057107810355495401116248
32울주군영남알프스레저(동굴나라)361215421874595773454948520120556842567402228730291503460389187203
33울주군옹기박물관00000234635028519712263514303640644
34울주군울산대곡박물관5145445354496034604956473443294992317141254092535530398
35울주군울산암각화박물관98321941688050190456852598875110024433452346559253593633
36울주군울산해양박물관5033429602146221562413289706214263350628163434120204
37울주군충렬공박제상기념관2524432585197913577541918399823149011230173363128032570