Overview

Dataset statistics

Number of variables8
Number of observations104
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory71.3 B

Variable types

Categorical1
Text1
Numeric6

Dataset

Description강릉, 경주, 부산, 여수, 전주 5개 지자체 관광지에 방문한 외지인을 대상으로 신한카드 라이프스테이지(가족구성) 비율 데이터 입니다.
Author한국철도공사
URLhttps://www.data.go.kr/data/15106046/fileData.do

Alerts

싱글 is highly overall correlated with 청소년자녀가족 and 2 other fieldsHigh correlation
청소년자녀가족 is highly overall correlated with 싱글High correlation
성인자녀가족 is highly overall correlated with 싱글High correlation
실버 is highly overall correlated with 싱글High correlation
청소년자녀가족 has unique valuesUnique
신혼 has 8 (7.7%) zerosZeros
영유아,어린이자녀가족 has 4 (3.8%) zerosZeros
성인자녀가족 has 2 (1.9%) zerosZeros
실버 has 2 (1.9%) zerosZeros

Reproduction

Analysis started2023-12-12 15:26:23.084785
Analysis finished2023-12-12 15:26:27.584129
Duration4.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지자체명
Categorical

Distinct5
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size964.0 B
부산시
32 
여수시
25 
경주시
16 
전주시
16 
강릉시
15 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산시 32
30.8%
여수시 25
24.0%
경주시 16
15.4%
전주시 16
15.4%
강릉시 15
14.4%

Length

2023-12-13T00:26:27.656026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:26:27.765734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산시 32
30.8%
여수시 25
24.0%
경주시 16
15.4%
전주시 16
15.4%
강릉시 15
14.4%

관광지명
Text

Distinct100
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-13T00:26:28.099782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.7980769
Min length2

Characters and Unicode

Total characters499
Distinct characters179
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)95.2%

Sample

1st row합계(중복제외)
2nd row강릉교동
3rd row강릉역앞
4th row강문해변
5th row경포호
ValueCountFrequency (%)
합계(중복제외 5
 
4.8%
거문도 1
 
1.0%
여서동사거리 1
 
1.0%
손죽도 1
 
1.0%
소호항 1
 
1.0%
백야도 1
 
1.0%
돌산우두리 1
 
1.0%
돌산도 1
 
1.0%
대여자도 1
 
1.0%
대두라도 1
 
1.0%
Other values (90) 90
86.5%
2023-12-13T00:26:28.856442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 19
 
3.8%
동 12
 
2.4%
대 11
 
2.2%
원 10
 
2.0%
포 10
 
2.0%
산 9
 
1.8%
리 9
 
1.8%
을 8
 
1.6%
수 8
 
1.6%
역 8
 
1.6%
Other values (169) 395
79.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
96.0%
Other Punctuation 10
 
2.0%
Open Punctuation 5
 
1.0%
Close Punctuation 5
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 19
 
4.0%
동 12
 
2.5%
대 11
 
2.3%
원 10
 
2.1%
포 10
 
2.1%
산 9
 
1.9%
리 9
 
1.9%
을 8
 
1.7%
수 8
 
1.7%
역 8
 
1.7%
Other values (165) 375
78.3%
Other Punctuation
ValueCountFrequency (%)
, 5
50.0%
. 5
50.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
96.0%
Common 20
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 19
 
4.0%
동 12
 
2.5%
대 11
 
2.3%
원 10
 
2.1%
포 10
 
2.1%
산 9
 
1.9%
리 9
 
1.9%
을 8
 
1.7%
수 8
 
1.7%
역 8
 
1.7%
Other values (165) 375
78.3%
Common
ValueCountFrequency (%)
, 5
25.0%
. 5
25.0%
( 5
25.0%
) 5
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
96.0%
ASCII 20
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 19
 
4.0%
동 12
 
2.5%
대 11
 
2.3%
원 10
 
2.1%
포 10
 
2.1%
산 9
 
1.9%
리 9
 
1.9%
을 8
 
1.7%
수 8
 
1.7%
역 8
 
1.7%
Other values (165) 375
78.3%
ASCII
ValueCountFrequency (%)
, 5
25.0%
. 5
25.0%
( 5
25.0%
) 5
25.0%

싱글
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.022618
Minimum14.285714
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:26:29.012717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.285714
5-th percentile20.870372
Q133.006223
median41.088963
Q349.115839
95-th percentile61.64239
Maximum75
Range60.714286
Interquartile range (IQR)16.109616

Descriptive statistics

Standard deviation12.204777
Coefficient of variation (CV)0.29751336
Kurtosis-0.05788633
Mean41.022618
Median Absolute Deviation (MAD)8.104422
Skewness0.12391837
Sum4266.3522
Variance148.95658
MonotonicityNot monotonic
2023-12-13T00:26:29.161314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53.84615384615385 2
 
1.9%
33.33333333333333 2
 
1.9%
46.84412250782376 1
 
1.0%
35.34971644612476 1
 
1.0%
18.181818181818183 1
 
1.0%
33.027905039566846 1
 
1.0%
48.333333333333336 1
 
1.0%
39.22506946588453 1
 
1.0%
41.72030427150381 1
 
1.0%
14.285714285714285 1
 
1.0%
Other values (92) 92
88.5%
ValueCountFrequency (%)
14.285714285714285 1
1.0%
16.0 1
1.0%
16.666666666666664 1
1.0%
17.520723436322534 1
1.0%
18.181818181818183 1
1.0%
20.625 1
1.0%
22.26081465108936 1
1.0%
23.482428115015974 1
1.0%
23.62204724409449 1
1.0%
24.193548387096776 1
1.0%
ValueCountFrequency (%)
75.0 1
1.0%
67.31391585760518 1
1.0%
65.65563725490196 1
1.0%
64.2928056125488 1
1.0%
63.85936222403925 1
1.0%
61.66666666666667 1
1.0%
61.50481898436867 1
1.0%
61.346153846153854 1
1.0%
58.080808080808076 1
1.0%
56.481481481481474 1
1.0%

신혼
Real number (ℝ)

ZEROS 

Distinct97
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8008082
Minimum0
Maximum8.0645161
Zeros8
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:26:29.353430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.1809024
median4.0085983
Q34.6886895
95-th percentile5.4386211
Maximum8.0645161
Range8.0645161
Interquartile range (IQR)1.5077871

Descriptive statistics

Standard deviation1.4935158
Coefficient of variation (CV)0.39294691
Kurtosis1.6090918
Mean3.8008082
Median Absolute Deviation (MAD)0.79356267
Skewness-0.90412059
Sum395.28405
Variance2.2305895
MonotonicityNot monotonic
2023-12-13T00:26:29.527399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
7.7%
3.9769330848482722 1
 
1.0%
2.2684310018903595 1
 
1.0%
4.652996845425868 1
 
1.0%
3.9235412474849096 1
 
1.0%
3.248646397334444 1
 
1.0%
3.3333333333333335 1
 
1.0%
4.847175054029021 1
 
1.0%
3.920421299005266 1
 
1.0%
4.0 1
 
1.0%
Other values (87) 87
83.7%
ValueCountFrequency (%)
0.0 8
7.7%
1.520912547528517 1
 
1.0%
1.9230769230769231 1
 
1.0%
2.127659574468085 1
 
1.0%
2.1739130434782608 1
 
1.0%
2.2684310018903595 1
 
1.0%
2.3529411764705883 1
 
1.0%
2.3972602739726026 1
 
1.0%
2.5559105431309903 1
 
1.0%
2.7210884353741496 1
 
1.0%
ValueCountFrequency (%)
8.064516129032258 1
1.0%
6.666666666666667 1
1.0%
6.185567010309279 1
1.0%
5.788635156664896 1
1.0%
5.678364189002487 1
1.0%
5.440785436694621 1
1.0%
5.426356589147287 1
1.0%
5.420267085624509 1
1.0%
5.2532914813846014 1
1.0%
5.246913580246913 1
1.0%

영유아,어린이자녀가족
Real number (ℝ)

ZEROS 

Distinct101
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.208492
Minimum0
Maximum24.875622
Zeros4
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:26:29.702042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.7066601
Q18.1545373
median9.5415069
Q311.614101
95-th percentile18.231016
Maximum24.875622
Range24.875622
Interquartile range (IQR)3.4595635

Descriptive statistics

Standard deviation4.2893057
Coefficient of variation (CV)0.42017034
Kurtosis1.8373104
Mean10.208492
Median Absolute Deviation (MAD)1.8062284
Skewness0.65535853
Sum1061.6832
Variance18.398144
MonotonicityNot monotonic
2023-12-13T00:26:29.843662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4
 
3.8%
9.631140335454832 1
 
1.0%
9.090909090909092 1
 
1.0%
10.995418575593503 1
 
1.0%
18.333333333333332 1
 
1.0%
17.767829577029946 1
 
1.0%
14.86249268578116 1
 
1.0%
16.0 1
 
1.0%
6.521739130434782 1
 
1.0%
11.627906976744185 1
 
1.0%
Other values (91) 91
87.5%
ValueCountFrequency (%)
0.0 4
3.8%
3.8461538461538463 1
 
1.0%
5.660377358490567 1
 
1.0%
5.9689288634505315 1
 
1.0%
6.076854334226988 1
 
1.0%
6.341911764705882 1
 
1.0%
6.401137980085349 1
 
1.0%
6.446910180610675 1
 
1.0%
6.481481481481481 1
 
1.0%
6.521739130434782 1
 
1.0%
ValueCountFrequency (%)
24.875621890547265 1
1.0%
21.875 1
1.0%
21.052631578947366 1
1.0%
20.078740157480315 1
1.0%
18.333333333333332 1
1.0%
18.251928020565554 1
1.0%
18.112513144058887 1
1.0%
17.767829577029946 1
1.0%
17.078479067981053 1
1.0%
16.99291961682632 1
1.0%

청소년자녀가족
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.132011
Minimum0
Maximum57.142857
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:26:29.998512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.801567
Q122.610959
median25.16772
Q328.524847
95-th percentile33.795902
Maximum57.142857
Range57.142857
Interquartile range (IQR)5.9138886

Descriptive statistics

Standard deviation6.7902948
Coefficient of variation (CV)0.2701851
Kurtosis5.5296845
Mean25.132011
Median Absolute Deviation (MAD)3.2718085
Skewness0.39628325
Sum2613.7291
Variance46.108104
MonotonicityNot monotonic
2023-12-13T00:26:30.180735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.411512359787615 1
 
1.0%
33.79804069329314 1
 
1.0%
25.93322818086225 1
 
1.0%
28.23608316566063 1
 
1.0%
9.090909090909092 1
 
1.0%
29.94585589337776 1
 
1.0%
23.333333333333332 1
 
1.0%
25.5634455078728 1
 
1.0%
26.506729081334115 1
 
1.0%
57.14285714285714 1
 
1.0%
Other values (94) 94
90.4%
ValueCountFrequency (%)
0.0 1
1.0%
9.090909090909092 1
1.0%
10.0 1
1.0%
13.268608414239482 1
1.0%
14.423076923076922 1
1.0%
15.789473684210526 1
1.0%
15.870098039215685 1
1.0%
16.387583559467867 1
1.0%
17.25265739983647 1
1.0%
17.424242424242426 1
1.0%
ValueCountFrequency (%)
57.14285714285714 1
1.0%
40.0 1
1.0%
37.5 1
1.0%
36.434108527131784 1
1.0%
34.89813994685562 1
1.0%
33.79804069329314 1
1.0%
33.78378378378378 1
1.0%
32.677165354330704 1
1.0%
32.35294117647059 1
1.0%
32.29684908789386 1
1.0%

성인자녀가족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct102
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.697254
Minimum0
Maximum28.571429
Zeros2
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:26:30.347093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.6685049
Q19.7194608
median12.024428
Q315.429843
95-th percentile21.84251
Maximum28.571429
Range28.571429
Interquartile range (IQR)5.7103817

Descriptive statistics

Standard deviation5.0253931
Coefficient of variation (CV)0.39578581
Kurtosis0.92344139
Mean12.697254
Median Absolute Deviation (MAD)2.6966439
Skewness0.51618589
Sum1320.5145
Variance25.254576
MonotonicityNot monotonic
2023-12-13T00:26:30.518610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.333333333333332 2
 
1.9%
0.0 2
 
1.9%
11.343577481627342 1
 
1.0%
11.627906976744185 1
 
1.0%
13.74916163648558 1
 
1.0%
18.181818181818183 1
 
1.0%
16.909620991253643 1
 
1.0%
5.0 1
 
1.0%
8.89163322012967 1
 
1.0%
8.543007606787596 1
 
1.0%
Other values (92) 92
88.5%
ValueCountFrequency (%)
0.0 2
1.9%
3.559870550161812 1
1.0%
5.0 1
1.0%
6.346153846153846 1
1.0%
6.666666666666667 1
1.0%
6.678921568627451 1
1.0%
6.8493150684931505 1
1.0%
6.850859881590077 1
1.0%
6.86835650040883 1
1.0%
6.944444444444445 1
1.0%
ValueCountFrequency (%)
28.57142857142857 1
1.0%
25.395629238884705 1
1.0%
25.0 1
1.0%
23.076923076923077 1
1.0%
23.003194888178914 1
1.0%
21.850331544047997 1
1.0%
21.798188874514874 1
1.0%
21.052631578947366 1
1.0%
20.967741935483872 1
1.0%
20.099079971691435 1
1.0%

실버
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct101
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1388165
Minimum0
Maximum45.454545
Zeros2
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T00:26:30.674814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.7613358
Q14.1502427
median5.6968283
Q38.1429368
95-th percentile19.533661
Maximum45.454545
Range45.454545
Interquartile range (IQR)3.992694

Descriptive statistics

Standard deviation6.1043316
Coefficient of variation (CV)0.85509014
Kurtosis15.737555
Mean7.1388165
Median Absolute Deviation (MAD)1.9235893
Skewness3.3519284
Sum742.43691
Variance37.262864
MonotonicityNot monotonic
2023-12-13T00:26:30.847911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.0 2
 
1.9%
1.6666666666666667 2
 
1.9%
0.0 2
 
1.9%
6.049149338374291 1
 
1.0%
5.7308096740273395 1
 
1.0%
4.862508383635144 1
 
1.0%
45.45454545454545 1
 
1.0%
5.872553102873803 1
 
1.0%
3.704847175054029 1
 
1.0%
4.447045055588063 1
 
1.0%
Other values (91) 91
87.5%
ValueCountFrequency (%)
0.0 2
1.9%
0.9708737864077669 1
1.0%
1.5487457806605334 1
1.0%
1.6666666666666667 2
1.9%
2.297794117647059 1
1.0%
2.5347506132461164 1
1.0%
2.9320987654320985 1
1.0%
2.9850746268656714 1
1.0%
3.1294051310967013 1
1.0%
3.1446540880503147 1
1.0%
ValueCountFrequency (%)
45.45454545454545 1
1.0%
25.0 2
1.9%
24.0 1
1.0%
20.0 1
1.0%
19.565217391304348 1
1.0%
19.35483870967742 1
1.0%
15.934065934065933 1
1.0%
15.384615384615385 1
1.0%
11.461951373539629 1
1.0%
11.126564673157164 1
1.0%

Interactions

2023-12-13T00:26:26.666753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:23.426073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.049747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.759153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.384817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.957775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.773696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:23.496454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.155269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.861363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.480394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.075538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.887773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:23.594387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.281148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.973244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.577667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.208846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.983827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:23.680206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.395054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.063342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.660904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.334219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.097632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:23.789104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.517306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.185827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.756900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.431334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:27.219899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:23.969398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:24.639472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.287116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:25.854934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:26:26.561280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:26:30.964108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체명관광지명싱글신혼영유아,어린이자녀가족청소년자녀가족성인자녀가족실버
지자체명1.0000.0000.5920.4030.5710.1790.3460.250
관광지명0.0001.0000.9900.9970.8431.0000.9930.988
싱글0.5920.9901.0000.5170.5500.8100.8230.597
신혼0.4030.9970.5171.0000.5180.5230.6050.482
영유아,어린이자녀가족0.5710.8430.5500.5181.0000.4690.6240.256
청소년자녀가족0.1791.0000.8100.5230.4691.0000.7170.610
성인자녀가족0.3460.9930.8230.6050.6240.7171.0000.635
실버0.2500.9880.5970.4820.2560.6100.6351.000
2023-12-13T00:26:31.080413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
싱글신혼영유아,어린이자녀가족청소년자녀가족성인자녀가족실버지자체명
싱글1.0000.112-0.311-0.787-0.673-0.6260.277
신혼0.1121.0000.279-0.085-0.194-0.3210.172
영유아,어린이자녀가족-0.3110.2791.0000.183-0.001-0.1040.264
청소년자녀가족-0.787-0.0850.1831.0000.4010.4110.098
성인자녀가족-0.673-0.194-0.0010.4011.0000.4500.144
실버-0.626-0.321-0.1040.4110.4501.0000.159
지자체명0.2770.1720.2640.0980.1440.1591.000

Missing values

2023-12-13T00:26:27.367346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:26:27.525839image/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

지자체명관광지명싱글신혼영유아,어린이자녀가족청소년자녀가족성인자녀가족실버
0강릉시합계(중복제외)46.8441233.9769339.6311423.41151211.3435774.792714
1강릉시강릉교동50.4222783.948879.03903224.0127829.4270713.149966
2강릉시강릉역앞47.7272733.8497228.9053822.40259712.0593695.055659
3강릉시강문해변55.3425434.48266110.628719.565836.850863.129405
4강릉시경포호55.0641743.752798.98437520.1729918.6774553.348214
5강릉시도깨비촬영지48.1958763.8659799.27835122.6804127.7319598.247423
6강릉시안목해변45.2284674.0032359.76546723.89809911.9894865.115245
7강릉시역전상권50.777484.5576419.32975921.07238610.0804294.182306
8강릉시영진항38.6018243.86452511.33304424.92401213.9817637.294833
9강릉시오죽헌49.049431.5209138.36501924.71482910.266166.08365
지자체명관광지명싱글신혼영유아,어린이자녀가족청소년자녀가족성인자녀가족실버
94전주시막걸리골목35.8974365.1282058.62470927.50582816.7832176.060606
95전주시세병호42.2680416.18556710.30927817.52577314.432999.278351
96전주시아중호수42.5531912.1276610.63829819.14893617.0212778.510638
97전주시완산공원40.4191623.74251510.92814424.25149714.8203595.838323
98전주시웨딩거리56.4814815.2469146.48148118.6728410.1851852.932099
99전주시자연생태관50.1369863.8356169.04109624.9315076.8493155.205479
100전주시전북도청41.3056824.3440919.19131228.40839411.8542154.896306
101전주시전주동물원26.8656723.48258724.87562226.36815915.4228862.985075
102전주시전주터미널42.8165012.844956.40113824.52347115.4765297.937411
103전주시한옥마을47.6450244.63012211.36242724.6141568.3688133.379457