Overview

Dataset statistics

Number of variables14
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.3 KiB
Average record size in memory115.3 B

Variable types

Numeric1
Categorical13

Alerts

examin_begin_de has constant value ""Constant
respond_id has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:09:31.410897
Analysis finished2023-12-10 10:09:34.425103
Duration3.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

respond_id
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53329930
Minimum53322367
Maximum53377311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:09:34.667279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53322367
5-th percentile53323085
Q153325962
median53328854
Q353331426
95-th percentile53333460
Maximum53377311
Range54944
Interquartile range (IQR)5464.75

Descriptive statistics

Standard deviation8926.5355
Coefficient of variation (CV)0.00016738322
Kurtosis22.233758
Mean53329930
Median Absolute Deviation (MAD)2671
Skewness4.5062906
Sum5.332993 × 109
Variance79683037
MonotonicityNot monotonic
2023-12-10T19:09:35.507921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53322367 1
 
1.0%
53330406 1
 
1.0%
53331008 1
 
1.0%
53330996 1
 
1.0%
53330987 1
 
1.0%
53330576 1
 
1.0%
53330460 1
 
1.0%
53330459 1
 
1.0%
53330444 1
 
1.0%
53330440 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
53322367 1
1.0%
53322541 1
1.0%
53322648 1
1.0%
53322965 1
1.0%
53323066 1
1.0%
53323086 1
1.0%
53323206 1
1.0%
53323229 1
1.0%
53323396 1
1.0%
53323513 1
1.0%
ValueCountFrequency (%)
53377311 1
1.0%
53377129 1
1.0%
53377085 1
1.0%
53333799 1
1.0%
53333464 1
1.0%
53333460 1
1.0%
53333389 1
1.0%
53333161 1
1.0%
53333009 1
1.0%
53332970 1
1.0%

examin_begin_de
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20220523
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20220523
2nd row20220523
3rd row20220523
4th row20220523
5th row20220523

Common Values

ValueCountFrequency (%)
20220523 100
100.0%

Length

2023-12-10T19:09:35.784121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:35.990400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20220523 100
100.0%

sexdstn_flag_cd
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
F
54 
M
46 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowF
3rd rowF
4th rowF
5th rowF

Common Values

ValueCountFrequency (%)
F 54
54.0%
M 46
46.0%

Length

2023-12-10T19:09:36.197989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:36.468225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 54
54.0%
m 46
46.0%

agrde_flag_nm
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
50대
25 
30대
24 
60대
20 
40대
17 
20대
14 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row60대
2nd row60대
3rd row60대
4th row50대
5th row50대

Common Values

ValueCountFrequency (%)
50대 25
25.0%
30대 24
24.0%
60대 20
20.0%
40대 17
17.0%
20대 14
14.0%

Length

2023-12-10T19:09:36.677536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:36.844558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50대 25
25.0%
30대 24
24.0%
60대 20
20.0%
40대 17
17.0%
20대 14
14.0%

answrr_oc_area_nm
Categorical

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
26 
경기도
26 
부산광역시
10 
대전광역시
7 
충청남도
5 
Other values (9)
26 

Length

Max length7
Median length5
Mean length4.34
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 26
26.0%
경기도 26
26.0%
부산광역시 10
 
10.0%
대전광역시 7
 
7.0%
충청남도 5
 
5.0%
경상북도 4
 
4.0%
충청북도 4
 
4.0%
인천광역시 4
 
4.0%
대구광역시 3
 
3.0%
제주특별자치도 3
 
3.0%
Other values (4) 8
 
8.0%

Length

2023-12-10T19:09:37.089276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 26
26.0%
경기도 26
26.0%
부산광역시 10
 
10.0%
대전광역시 7
 
7.0%
충청남도 5
 
5.0%
경상북도 4
 
4.0%
충청북도 4
 
4.0%
인천광역시 4
 
4.0%
대구광역시 3
 
3.0%
제주특별자치도 3
 
3.0%
Other values (4) 8
 
8.0%

hshld_income_dgree_nm
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
300이상500만원 미만
29 
500이상700만원 미만
28 
300만원 미만
22 
700만원 이상
15 
무응답
6 

Length

Max length13
Median length13
Mean length10.55
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row300이상500만원 미만
2nd row700만원 이상
3rd row700만원 이상
4th row500이상700만원 미만
5th row300만원 미만

Common Values

ValueCountFrequency (%)
300이상500만원 미만 29
29.0%
500이상700만원 미만 28
28.0%
300만원 미만 22
22.0%
700만원 이상 15
15.0%
무응답 6
 
6.0%

Length

2023-12-10T19:09:37.342367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:37.546116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 79
40.7%
300이상500만원 29
 
14.9%
500이상700만원 28
 
14.4%
300만원 22
 
11.3%
700만원 15
 
7.7%
이상 15
 
7.7%
무응답 6
 
3.1%

cltur_art_viewng_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷하다
45 
조금 커졌다
32 
조금 작아졌다
16 
매우 커졌다
 
4
매우 작아졌다
 
3

Length

Max length7
Median length6
Mean length5.29
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비슷하다
2nd row조금 커졌다
3rd row조금 커졌다
4th row조금 커졌다
5th row비슷하다

Common Values

ValueCountFrequency (%)
비슷하다 45
45.0%
조금 커졌다 32
32.0%
조금 작아졌다 16
 
16.0%
매우 커졌다 4
 
4.0%
매우 작아졌다 3
 
3.0%

Length

2023-12-10T19:09:37.756868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:37.965567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조금 48
31.0%
비슷하다 45
29.0%
커졌다 36
23.2%
작아졌다 19
 
12.3%
매우 7
 
4.5%

cltur_art_act_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷하다
51 
조금 커졌다
22 
조금 작아졌다
16 
매우 작아졌다
7 
매우 커졌다
 
4

Length

Max length7
Median length4
Mean length5.21
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비슷하다
2nd row조금 커졌다
3rd row조금 작아졌다
4th row비슷하다
5th row비슷하다

Common Values

ValueCountFrequency (%)
비슷하다 51
51.0%
조금 커졌다 22
22.0%
조금 작아졌다 16
 
16.0%
매우 작아졌다 7
 
7.0%
매우 커졌다 4
 
4.0%

Length

2023-12-10T19:09:38.216341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:38.424078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비슷하다 51
34.2%
조금 38
25.5%
커졌다 26
17.4%
작아졌다 23
15.4%
매우 11
 
7.4%

sports_viewng_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷하다
46 
조금 커졌다
30 
조금 작아졌다
17 
매우 작아졌다
5 
매우 커졌다
 
2

Length

Max length7
Median length6
Mean length5.3
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비슷하다
2nd row조금 커졌다
3rd row조금 커졌다
4th row비슷하다
5th row비슷하다

Common Values

ValueCountFrequency (%)
비슷하다 46
46.0%
조금 커졌다 30
30.0%
조금 작아졌다 17
 
17.0%
매우 작아졌다 5
 
5.0%
매우 커졌다 2
 
2.0%

Length

2023-12-10T19:09:38.667552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:38.920268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조금 47
30.5%
비슷하다 46
29.9%
커졌다 32
20.8%
작아졌다 22
14.3%
매우 7
 
4.5%

sports_act_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
조금 커졌다
43 
비슷하다
39 
조금 작아졌다
9 
매우 작아졌다
5 
매우 커졌다
 
4

Length

Max length7
Median length6
Mean length5.36
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조금 커졌다
2nd row조금 커졌다
3rd row매우 커졌다
4th row비슷하다
5th row비슷하다

Common Values

ValueCountFrequency (%)
조금 커졌다 43
43.0%
비슷하다 39
39.0%
조금 작아졌다 9
 
9.0%
매우 작아졌다 5
 
5.0%
매우 커졌다 4
 
4.0%

Length

2023-12-10T19:09:39.163581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:39.429568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조금 52
32.3%
커졌다 47
29.2%
비슷하다 39
24.2%
작아졌다 14
 
8.7%
매우 9
 
5.6%

tursm_tour_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
조금 커졌다
47 
비슷하다
27 
매우 커졌다
16 
조금 작아졌다
6 
매우 작아졌다
 
4

Length

Max length7
Median length6
Mean length5.56
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조금 커졌다
2nd row조금 커졌다
3rd row매우 커졌다
4th row조금 커졌다
5th row조금 작아졌다

Common Values

ValueCountFrequency (%)
조금 커졌다 47
47.0%
비슷하다 27
27.0%
매우 커졌다 16
 
16.0%
조금 작아졌다 6
 
6.0%
매우 작아졌다 4
 
4.0%

Length

2023-12-10T19:09:39.826408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:40.068071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
커졌다 63
36.4%
조금 53
30.6%
비슷하다 27
15.6%
매우 20
 
11.6%
작아졌다 10
 
5.8%

rcrt_rest_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷하다
49 
조금 커졌다
37 
매우 커졌다
7 
조금 작아졌다
6 
매우 작아졌다
 
1

Length

Max length7
Median length6
Mean length5.09
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row비슷하다
2nd row조금 작아졌다
3rd row조금 커졌다
4th row조금 커졌다
5th row비슷하다

Common Values

ValueCountFrequency (%)
비슷하다 49
49.0%
조금 커졌다 37
37.0%
매우 커졌다 7
 
7.0%
조금 작아졌다 6
 
6.0%
매우 작아졌다 1
 
1.0%

Length

2023-12-10T19:09:40.307571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:40.534274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비슷하다 49
32.5%
커졌다 44
29.1%
조금 43
28.5%
매우 8
 
5.3%
작아졌다 7
 
4.6%

self_impt_self_manage_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷하다
47 
조금 커졌다
37 
조금 작아졌다
12 
매우 커졌다
 
3
매우 작아졌다
 
1

Length

Max length7
Median length6
Mean length5.19
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row조금 작아졌다
2nd row조금 커졌다
3rd row비슷하다
4th row비슷하다
5th row조금 커졌다

Common Values

ValueCountFrequency (%)
비슷하다 47
47.0%
조금 커졌다 37
37.0%
조금 작아졌다 12
 
12.0%
매우 커졌다 3
 
3.0%
매우 작아졌다 1
 
1.0%

Length

2023-12-10T19:09:40.741036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:40.952017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조금 49
32.0%
비슷하다 47
30.7%
커졌다 40
26.1%
작아졌다 13
 
8.5%
매우 4
 
2.6%

sct_exchg_intrst_dgree_value
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷하다
56 
조금 커졌다
25 
조금 작아졌다
12 
매우 작아졌다
 
4
매우 커졌다
 
3

Length

Max length7
Median length4
Mean length5.04
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조금 커졌다
2nd row조금 커졌다
3rd row조금 작아졌다
4th row비슷하다
5th row조금 작아졌다

Common Values

ValueCountFrequency (%)
비슷하다 56
56.0%
조금 커졌다 25
25.0%
조금 작아졌다 12
 
12.0%
매우 작아졌다 4
 
4.0%
매우 커졌다 3
 
3.0%

Length

2023-12-10T19:09:41.161813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:09:41.357622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비슷하다 56
38.9%
조금 37
25.7%
커졌다 28
19.4%
작아졌다 16
 
11.1%
매우 7
 
4.9%

Interactions

2023-12-10T19:09:33.385037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:09:41.525051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmcltur_art_viewng_intrst_dgree_valuecltur_art_act_intrst_dgree_valuesports_viewng_intrst_dgree_valuesports_act_intrst_dgree_valuetursm_tour_intrst_dgree_valuercrt_rest_intrst_dgree_valueself_impt_self_manage_intrst_dgree_valuesct_exchg_intrst_dgree_value
respond_id1.0000.2080.2370.5790.1990.3900.1670.2710.2110.1560.0000.0000.000
sexdstn_flag_cd0.2081.0000.0000.0000.0000.0000.1090.0000.0000.0000.0000.0000.000
agrde_flag_nm0.2370.0001.0000.2570.5250.0000.0000.2760.0000.0000.0000.2890.000
answrr_oc_area_nm0.5790.0000.2571.0000.3950.1060.3260.3850.0000.4460.0000.3940.545
hshld_income_dgree_nm0.1990.0000.5250.3951.0000.4570.4360.2040.1350.3010.0000.0000.410
cltur_art_viewng_intrst_dgree_value0.3900.0000.0000.1060.4571.0000.8480.8040.7090.7630.6230.2140.602
cltur_art_act_intrst_dgree_value0.1670.1090.0000.3260.4360.8481.0000.8370.7520.6830.6050.5920.690
sports_viewng_intrst_dgree_value0.2710.0000.2760.3850.2040.8040.8371.0000.8150.6380.3590.5890.581
sports_act_intrst_dgree_value0.2110.0000.0000.0000.1350.7090.7520.8151.0000.6050.0000.1050.467
tursm_tour_intrst_dgree_value0.1560.0000.0000.4460.3010.7630.6830.6380.6051.0000.5870.5800.854
rcrt_rest_intrst_dgree_value0.0000.0000.0000.0000.0000.6230.6050.3590.0000.5871.0000.6510.665
self_impt_self_manage_intrst_dgree_value0.0000.0000.2890.3940.0000.2140.5920.5890.1050.5800.6511.0000.615
sct_exchg_intrst_dgree_value0.0000.0000.0000.5450.4100.6020.6900.5810.4670.8540.6650.6151.000
2023-12-10T19:09:41.927517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
hshld_income_dgree_nmcltur_art_act_intrst_dgree_valuetursm_tour_intrst_dgree_valuesports_viewng_intrst_dgree_valueself_impt_self_manage_intrst_dgree_valuecltur_art_viewng_intrst_dgree_valuesexdstn_flag_cdagrde_flag_nmsports_act_intrst_dgree_valuercrt_rest_intrst_dgree_valuesct_exchg_intrst_dgree_valueanswrr_oc_area_nm
hshld_income_dgree_nm1.0000.1740.1150.0740.0000.1840.0000.2180.0470.0000.1620.205
cltur_art_act_intrst_dgree_value0.1741.0000.3170.4680.2550.4830.1300.0000.3740.2640.3210.164
tursm_tour_intrst_dgree_value0.1150.3171.0000.2850.2490.3850.0000.0000.2630.2530.4920.237
sports_viewng_intrst_dgree_value0.0740.4680.2851.0000.2540.4280.0000.1040.4400.1390.2490.199
self_impt_self_manage_intrst_dgree_value0.0000.2550.2490.2541.0000.0790.0000.1100.0340.2930.2700.204
cltur_art_viewng_intrst_dgree_value0.1840.4830.3850.4280.0791.0000.0000.0000.3360.2750.2610.038
sexdstn_flag_cd0.0000.1300.0000.0000.0000.0001.0000.0000.0000.0000.0000.000
agrde_flag_nm0.2180.0000.0000.1040.1100.0000.0001.0000.0000.0000.0000.125
sports_act_intrst_dgree_value0.0470.3740.2630.4400.0340.3360.0000.0001.0000.0000.1890.000
rcrt_rest_intrst_dgree_value0.0000.2640.2530.1390.2930.2750.0000.0000.0001.0000.3030.000
sct_exchg_intrst_dgree_value0.1620.3210.4920.2490.2700.2610.0000.0000.1890.3031.0000.304
answrr_oc_area_nm0.2050.1640.2370.1990.2040.0380.0000.1250.0000.0000.3041.000
2023-12-10T19:09:42.219764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmcltur_art_viewng_intrst_dgree_valuecltur_art_act_intrst_dgree_valuesports_viewng_intrst_dgree_valuesports_act_intrst_dgree_valuetursm_tour_intrst_dgree_valuercrt_rest_intrst_dgree_valueself_impt_self_manage_intrst_dgree_valuesct_exchg_intrst_dgree_value
respond_id1.0000.1440.1930.3510.1550.3230.1360.2190.1710.1320.0000.0000.000
sexdstn_flag_cd0.1441.0000.0000.0000.0000.0000.1300.0000.0000.0000.0000.0000.000
agrde_flag_nm0.1930.0001.0000.1250.2180.0000.0000.1040.0000.0000.0000.1100.000
answrr_oc_area_nm0.3510.0000.1251.0000.2050.0380.1640.1990.0000.2370.0000.2040.304
hshld_income_dgree_nm0.1550.0000.2180.2051.0000.1840.1740.0740.0470.1150.0000.0000.162
cltur_art_viewng_intrst_dgree_value0.3230.0000.0000.0380.1841.0000.4830.4280.3360.3850.2750.0790.261
cltur_art_act_intrst_dgree_value0.1360.1300.0000.1640.1740.4831.0000.4680.3740.3170.2640.2550.321
sports_viewng_intrst_dgree_value0.2190.0000.1040.1990.0740.4280.4681.0000.4400.2850.1390.2540.249
sports_act_intrst_dgree_value0.1710.0000.0000.0000.0470.3360.3740.4401.0000.2630.0000.0340.189
tursm_tour_intrst_dgree_value0.1320.0000.0000.2370.1150.3850.3170.2850.2631.0000.2530.2490.492
rcrt_rest_intrst_dgree_value0.0000.0000.0000.0000.0000.2750.2640.1390.0000.2531.0000.2930.303
self_impt_self_manage_intrst_dgree_value0.0000.0000.1100.2040.0000.0790.2550.2540.0340.2490.2931.0000.270
sct_exchg_intrst_dgree_value0.0000.0000.0000.3040.1620.2610.3210.2490.1890.4920.3030.2701.000

Missing values

2023-12-10T19:09:33.663747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:09:34.223827image/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

respond_idexamin_begin_desexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmcltur_art_viewng_intrst_dgree_valuecltur_art_act_intrst_dgree_valuesports_viewng_intrst_dgree_valuesports_act_intrst_dgree_valuetursm_tour_intrst_dgree_valuercrt_rest_intrst_dgree_valueself_impt_self_manage_intrst_dgree_valuesct_exchg_intrst_dgree_value
05332236720220523M60대서울특별시300이상500만원 미만비슷하다비슷하다비슷하다조금 커졌다조금 커졌다비슷하다조금 작아졌다조금 커졌다
15337708520220523F60대서울특별시700만원 이상조금 커졌다조금 커졌다조금 커졌다조금 커졌다조금 커졌다조금 작아졌다조금 커졌다조금 커졌다
25332254120220523F60대서울특별시700만원 이상조금 커졌다조금 작아졌다조금 커졌다매우 커졌다매우 커졌다조금 커졌다비슷하다조금 작아졌다
35332264820220523F50대서울특별시500이상700만원 미만조금 커졌다비슷하다비슷하다비슷하다조금 커졌다조금 커졌다비슷하다비슷하다
45332296520220523F50대서울특별시300만원 미만비슷하다비슷하다비슷하다비슷하다조금 작아졌다비슷하다조금 커졌다조금 작아졌다
55332306620220523M30대서울특별시700만원 이상조금 커졌다조금 커졌다조금 커졌다비슷하다매우 커졌다매우 커졌다조금 작아졌다비슷하다
65332308620220523F60대서울특별시500이상700만원 미만조금 작아졌다조금 작아졌다조금 커졌다조금 커졌다조금 커졌다조금 커졌다비슷하다조금 커졌다
75337712920220523F20대부산광역시무응답비슷하다비슷하다비슷하다비슷하다비슷하다조금 커졌다조금 커졌다비슷하다
85332320620220523F30대충청남도300만원 미만조금 커졌다비슷하다비슷하다조금 커졌다조금 커졌다조금 커졌다조금 커졌다비슷하다
95332322920220523M40대서울특별시700만원 이상비슷하다비슷하다비슷하다비슷하다비슷하다비슷하다조금 커졌다조금 작아졌다
respond_idexamin_begin_desexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmcltur_art_viewng_intrst_dgree_valuecltur_art_act_intrst_dgree_valuesports_viewng_intrst_dgree_valuesports_act_intrst_dgree_valuetursm_tour_intrst_dgree_valuercrt_rest_intrst_dgree_valueself_impt_self_manage_intrst_dgree_valuesct_exchg_intrst_dgree_value
905333246220220523F50대충청남도500이상700만원 미만조금 작아졌다조금 작아졌다조금 작아졌다조금 작아졌다조금 커졌다조금 작아졌다조금 커졌다비슷하다
915333259220220523F40대경기도500이상700만원 미만비슷하다비슷하다비슷하다비슷하다비슷하다비슷하다비슷하다비슷하다
925333277820220523M60대경상북도300이상500만원 미만비슷하다조금 작아졌다조금 커졌다조금 커졌다비슷하다비슷하다비슷하다비슷하다
935333297020220523M30대부산광역시300만원 미만비슷하다조금 커졌다조금 커졌다매우 커졌다조금 커졌다조금 커졌다조금 커졌다조금 커졌다
945333300920220523F40대경기도300이상500만원 미만비슷하다비슷하다비슷하다비슷하다비슷하다비슷하다비슷하다비슷하다
955333316120220523F30대경상남도500이상700만원 미만조금 작아졌다조금 작아졌다조금 작아졌다조금 커졌다조금 커졌다조금 커졌다조금 커졌다조금 작아졌다
965333338920220523F60대전라북도300만원 미만매우 작아졌다매우 작아졌다매우 작아졌다매우 작아졌다매우 작아졌다조금 커졌다조금 커졌다매우 작아졌다
975333346020220523M30대경기도500이상700만원 미만매우 작아졌다매우 작아졌다매우 작아졌다매우 작아졌다매우 커졌다비슷하다비슷하다비슷하다
985333346420220523M60대인천광역시300이상500만원 미만조금 커졌다비슷하다비슷하다조금 커졌다조금 커졌다조금 커졌다비슷하다비슷하다
995333379920220523M60대전라북도300만원 미만조금 커졌다조금 커졌다조금 커졌다조금 커졌다조금 커졌다매우 커졌다조금 커졌다조금 커졌다