Overview

Dataset statistics

Number of variables6
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory57.5 B

Variable types

Text1
Numeric4
DateTime1

Dataset

Description광주광역시도시공사에서 관리하는 실내빙상장의 입장객 현황에 대한 데이터로 월별 성인 입장객 수, 청소년 입장객 수, 어린이 입장객 수 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15103731/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
성인 is highly overall correlated with 청소년 and 2 other fieldsHigh correlation
청소년 is highly overall correlated with 성인 and 2 other fieldsHigh correlation
어린이 is highly overall correlated with 성인 and 2 other fieldsHigh correlation
월별 일일입장 인원 is highly overall correlated with 성인 and 2 other fieldsHigh correlation
구분 has unique valuesUnique
성인 has unique valuesUnique
청소년 has unique valuesUnique
어린이 has unique valuesUnique
월별 일일입장 인원 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:11:07.119457
Analysis finished2023-12-12 16:11:09.037247
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T01:11:09.136549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.25
Min length8

Characters and Unicode

Total characters198
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row2021년 1월
2nd row2021년 2월
3rd row2021년 3월
4th row2021년 4월
5th row2021년 5월
ValueCountFrequency (%)
2021년 12
25.0%
2022년 12
25.0%
1월 2
 
4.2%
2월 2
 
4.2%
3월 2
 
4.2%
4월 2
 
4.2%
5월 2
 
4.2%
6월 2
 
4.2%
7월 2
 
4.2%
8월 2
 
4.2%
Other values (4) 8
16.7%
2023-12-13T01:11:09.492827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 64
32.3%
0 26
13.1%
년 24
 
12.1%
24
 
12.1%
월 24
 
12.1%
1 22
 
11.1%
3 2
 
1.0%
4 2
 
1.0%
5 2
 
1.0%
6 2
 
1.0%
Other values (3) 6
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
63.6%
Other Letter 48
 
24.2%
Space Separator 24
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 64
50.8%
0 26
20.6%
1 22
 
17.5%
3 2
 
1.6%
4 2
 
1.6%
5 2
 
1.6%
6 2
 
1.6%
7 2
 
1.6%
8 2
 
1.6%
9 2
 
1.6%
Other Letter
ValueCountFrequency (%)
년 24
50.0%
월 24
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150
75.8%
Hangul 48
 
24.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 64
42.7%
0 26
17.3%
24
 
16.0%
1 22
 
14.7%
3 2
 
1.3%
4 2
 
1.3%
5 2
 
1.3%
6 2
 
1.3%
7 2
 
1.3%
8 2
 
1.3%
Hangul
ValueCountFrequency (%)
년 24
50.0%
월 24
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150
75.8%
Hangul 48
 
24.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 64
42.7%
0 26
17.3%
24
 
16.0%
1 22
 
14.7%
3 2
 
1.3%
4 2
 
1.3%
5 2
 
1.3%
6 2
 
1.3%
7 2
 
1.3%
8 2
 
1.3%
Hangul
ValueCountFrequency (%)
년 24
50.0%
월 24
50.0%

성인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1820.1667
Minimum713
Maximum4930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T01:11:09.660253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum713
5-th percentile884.15
Q11034.5
median1194
Q32508
95-th percentile3473.75
Maximum4930
Range4217
Interquartile range (IQR)1473.5

Descriptive statistics

Standard deviation1086.8344
Coefficient of variation (CV)0.5971071
Kurtosis1.2569037
Mean1820.1667
Median Absolute Deviation (MAD)346.5
Skewness1.2564316
Sum43684
Variance1181209.1
MonotonicityNot monotonic
2023-12-13T01:11:10.110161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1114 1
 
4.2%
4930 1
 
4.2%
2965 1
 
4.2%
1203 1
 
4.2%
1127 1
 
4.2%
1104 1
 
4.2%
3206 1
 
4.2%
2497 1
 
4.2%
1577 1
 
4.2%
1168 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
713 1
4.2%
884 1
4.2%
885 1
4.2%
909 1
4.2%
913 1
4.2%
952 1
4.2%
1062 1
4.2%
1104 1
4.2%
1114 1
4.2%
1127 1
4.2%
ValueCountFrequency (%)
4930 1
4.2%
3521 1
4.2%
3206 1
4.2%
2965 1
4.2%
2922 1
4.2%
2541 1
4.2%
2497 1
4.2%
2429 1
4.2%
2116 1
4.2%
1761 1
4.2%

청소년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1169.7917
Minimum185
Maximum3618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T01:11:10.234915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185
5-th percentile262.7
Q1480
median980.5
Q31920.25
95-th percentile2456.85
Maximum3618
Range3433
Interquartile range (IQR)1440.25

Descriptive statistics

Standard deviation861.97846
Coefficient of variation (CV)0.73686494
Kurtosis1.2201844
Mean1169.7917
Median Absolute Deviation (MAD)537
Skewness1.1698246
Sum28075
Variance743006.87
MonotonicityNot monotonic
2023-12-13T01:11:10.353423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
547 1
 
4.2%
3618 1
 
4.2%
2508 1
 
4.2%
618 1
 
4.2%
958 1
 
4.2%
468 1
 
4.2%
1917 1
 
4.2%
1939 1
 
4.2%
927 1
 
4.2%
1153 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
185 1
4.2%
251 1
4.2%
329 1
4.2%
385 1
4.2%
419 1
4.2%
468 1
4.2%
484 1
4.2%
547 1
4.2%
618 1
4.2%
733 1
4.2%
ValueCountFrequency (%)
3618 1
4.2%
2508 1
4.2%
2167 1
4.2%
2115 1
4.2%
1939 1
4.2%
1930 1
4.2%
1917 1
4.2%
1199 1
4.2%
1153 1
4.2%
1148 1
4.2%

어린이
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1335.4167
Minimum338
Maximum4256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T01:11:10.486324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum338
5-th percentile372.55
Q1691.5
median1075.5
Q31635.75
95-th percentile2762.3
Maximum4256
Range3918
Interquartile range (IQR)944.25

Descriptive statistics

Standard deviation926.39352
Coefficient of variation (CV)0.69371121
Kurtosis3.0362504
Mean1335.4167
Median Absolute Deviation (MAD)518.5
Skewness1.5666031
Sum32050
Variance858204.95
MonotonicityNot monotonic
2023-12-13T01:11:10.612590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
438 1
 
4.2%
2109 1
 
4.2%
4256 1
 
4.2%
2560 1
 
4.2%
1071 1
 
4.2%
1051 1
 
4.2%
2798 1
 
4.2%
2158 1
 
4.2%
1598 1
 
4.2%
1486 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
338 1
4.2%
361 1
4.2%
438 1
4.2%
515 1
4.2%
561 1
4.2%
684 1
4.2%
694 1
4.2%
771 1
4.2%
780 1
4.2%
833 1
4.2%
ValueCountFrequency (%)
4256 1
4.2%
2798 1
4.2%
2560 1
4.2%
2158 1
4.2%
2109 1
4.2%
1722 1
4.2%
1607 1
4.2%
1598 1
4.2%
1486 1
4.2%
1395 1
4.2%

월별 일일입장 인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4325.375
Minimum1259
Maximum10657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T01:11:10.731447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1259
5-th percentile1625.45
Q12263.25
median3663
Q36097.75
95-th percentile9457.8
Maximum10657
Range9398
Interquartile range (IQR)3834.5

Descriptive statistics

Standard deviation2623.8159
Coefficient of variation (CV)0.60661004
Kurtosis0.2260074
Mean4325.375
Median Absolute Deviation (MAD)1555
Skewness1.0115624
Sum103809
Variance6884409.9
MonotonicityNot monotonic
2023-12-13T01:11:10.849932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2099 1
 
4.2%
10657 1
 
4.2%
9729 1
 
4.2%
4381 1
 
4.2%
3156 1
 
4.2%
2623 1
 
4.2%
7921 1
 
4.2%
6594 1
 
4.2%
4102 1
 
4.2%
3807 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1259 1
4.2%
1580 1
4.2%
1883 1
4.2%
1997 1
4.2%
2099 1
4.2%
2117 1
4.2%
2312 1
4.2%
2314 1
4.2%
2623 1
4.2%
2683 1
4.2%
ValueCountFrequency (%)
10657 1
4.2%
9729 1
4.2%
7921 1
4.2%
7295 1
4.2%
6594 1
4.2%
6574 1
4.2%
5939 1
4.2%
4873 1
4.2%
4395 1
4.2%
4381 1
4.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T01:11:10.969191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:11.078121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:11:08.407618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.305624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.653899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:08.049067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:08.503815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.397828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.739250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:08.129178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:08.599064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.483327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.840393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:08.224871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:08.711785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.568907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:07.959080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:11:08.326650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:11:11.168887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분성인청소년어린이월별 일일입장 인원
구분1.0001.0001.0001.0001.000
성인1.0001.0000.7230.7940.717
청소년1.0000.7231.0000.7660.797
어린이1.0000.7940.7661.0000.709
월별 일일입장 인원1.0000.7170.7970.7091.000
2023-12-13T01:11:11.270922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성인청소년어린이월별 일일입장 인원
성인1.0000.8320.7980.922
청소년0.8321.0000.7660.930
어린이0.7980.7661.0000.918
월별 일일입장 인원0.9220.9300.9181.000

Missing values

2023-12-13T01:11:08.849770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:11:08.979284image/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

구분성인청소년어린이월별 일일입장 인원데이터기준일자
02021년 1월111454743820992022-12-31
12021년 2월1761107468435192022-12-31
22021년 3월91332933815802022-12-31
32021년 4월71318536112592022-12-31
42021년 5월88448451518832022-12-31
52021년 6월118525156119972022-12-31
62021년 7월21161199108043952022-12-31
72021년 8월29221930172265742022-12-31
82021년 9월95238578021172022-12-31
92021년 10월88573369423122022-12-31
구분성인청소년어린이월별 일일입장 인원데이터기준일자
142022년 3월25411148118448732022-12-31
152022년 4월106241983323142022-12-31
162022년 5월11681153148638072022-12-31
172022년 6월1577927159841022022-12-31
182022년 7월24971939215865942022-12-31
192022년 8월32061917279879212022-12-31
202022년 9월1104468105126232022-12-31
212022년 10월1127958107131562022-12-31
222022년 11월1203618256043812022-12-31
232022년 12월29652508425697292022-12-31