Overview

Dataset statistics

Number of variables15
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory123.3 B

Variable types

Numeric1
Categorical14

Alerts

examin_begin_de has constant value ""Constant
dmstc_ecnm_future_prspect_value is highly overall correlated with jb_future_prspect_value and 2 other fieldsHigh correlation
jb_future_prspect_value is highly overall correlated with dmstc_ecnm_future_prspect_valueHigh correlation
stdolv_future_prspect_value is highly overall correlated with income_future_prspect_value and 2 other fieldsHigh correlation
income_future_prspect_value is highly overall correlated with dmstc_ecnm_future_prspect_value and 4 other fieldsHigh correlation
spnd_expndtr_rmnpw_future_prspect_value is highly overall correlated with dmstc_ecnm_future_prspect_value and 3 other fieldsHigh correlation
svings_rmnpw_future_prspect_value is highly overall correlated with stdolv_future_prspect_value and 3 other fieldsHigh correlation
debt_scale_future_prspect_value is highly overall correlated with income_future_prspect_value and 1 other fieldsHigh correlation
respond_id has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:17:53.574486
Analysis finished2023-12-10 10:17:55.822957
Duration2.25 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%
Mean318657.95
Minimum4065
Maximum1146802
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:17:55.928443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4065
5-th percentile30540.2
Q1219295.75
median340890
Q3409642.5
95-th percentile444638.25
Maximum1146802
Range1142737
Interquartile range (IQR)190346.75

Descriptive statistics

Standard deviation188980.78
Coefficient of variation (CV)0.59305216
Kurtosis6.722029
Mean318657.95
Median Absolute Deviation (MAD)80568
Skewness1.6487939
Sum31865795
Variance3.5713737 × 1010
MonotonicityNot monotonic
2023-12-10T19:17:56.176332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4065 1
 
1.0%
382667 1
 
1.0%
409280 1
 
1.0%
409165 1
 
1.0%
405917 1
 
1.0%
403174 1
 
1.0%
398652 1
 
1.0%
397295 1
 
1.0%
396550 1
 
1.0%
394487 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
4065 1
1.0%
9357 1
1.0%
12856 1
1.0%
18328 1
1.0%
27618 1
1.0%
30694 1
1.0%
37619 1
1.0%
47792 1
1.0%
50946 1
1.0%
69355 1
1.0%
ValueCountFrequency (%)
1146802 1
1.0%
1081578 1
1.0%
1034791 1
1.0%
444789 1
1.0%
444643 1
1.0%
444638 1
1.0%
444145 1
1.0%
443562 1
1.0%
443086 1
1.0%
442690 1
1.0%

examin_begin_de
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20211103
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20211103
2nd row20211103
3rd row20211103
4th row20211103
5th row20211103

Common Values

ValueCountFrequency (%)
20211103 100
100.0%

Length

2023-12-10T19:17:56.396645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:56.523988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20211103 100
100.0%

sexdstn_flag_cd
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
F
53 
M
47 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 53
53.0%
M 47
47.0%

Length

2023-12-10T19:17:56.639861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:56.757935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 53
53.0%
m 47
47.0%

agrde_flag_nm
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20대
34 
30대
28 
50대
18 
40대
12 
60대
8 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30대
2nd row20대
3rd row60대
4th row40대
5th row30대

Common Values

ValueCountFrequency (%)
20대 34
34.0%
30대 28
28.0%
50대 18
18.0%
40대 12
 
12.0%
60대 8
 
8.0%

Length

2023-12-10T19:17:56.934382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:57.120919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 34
34.0%
30대 28
28.0%
50대 18
18.0%
40대 12
 
12.0%
60대 8
 
8.0%

answrr_oc_area_nm
Categorical

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
25 
경기도
21 
인천광역시
10 
대구광역시
7 
부산광역시
5 
Other values (12)
32 

Length

Max length7
Median length5
Mean length4.38
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row부산광역시
2nd row대전광역시
3rd row서울특별시
4th row서울특별시
5th row경기도

Common Values

ValueCountFrequency (%)
서울특별시 25
25.0%
경기도 21
21.0%
인천광역시 10
 
10.0%
대구광역시 7
 
7.0%
부산광역시 5
 
5.0%
전라북도 5
 
5.0%
경상북도 5
 
5.0%
충청북도 5
 
5.0%
대전광역시 4
 
4.0%
충청남도 3
 
3.0%
Other values (7) 10
 
10.0%

Length

2023-12-10T19:17:57.340999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 25
25.0%
경기도 21
21.0%
인천광역시 10
 
10.0%
대구광역시 7
 
7.0%
부산광역시 5
 
5.0%
전라북도 5
 
5.0%
경상북도 5
 
5.0%
충청북도 5
 
5.0%
대전광역시 4
 
4.0%
충청남도 3
 
3.0%
Other values (7) 10
 
10.0%

hshld_income_dgree_nm
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
200만원이하
43 
모름/무응답
27 
200만원초과400만원이하
22 
400만원초과700만원이하
8 

Length

Max length14
Median length7
Mean length8.83
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row400만원초과700만원이하
2nd row모름/무응답
3rd row200만원이하
4th row200만원초과400만원이하
5th row200만원초과400만원이하

Common Values

ValueCountFrequency (%)
200만원이하 43
43.0%
모름/무응답 27
27.0%
200만원초과400만원이하 22
22.0%
400만원초과700만원이하 8
 
8.0%

Length

2023-12-10T19:17:57.573500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:57.749234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200만원이하 43
43.0%
모름/무응답 27
27.0%
200만원초과400만원이하 22
22.0%
400만원초과700만원이하 8
 
8.0%

labor_empmn_stle_nm
Categorical

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
정규직근로자
59 
비정규직/일용직근로자
15 
무직/퇴직
14 
사업자
 
5
학생
 
4

Length

Max length11
Median length6
Mean length6.24
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업자
2nd row전업주부
3rd row전업주부
4th row정규직근로자
5th row정규직근로자

Common Values

ValueCountFrequency (%)
정규직근로자 59
59.0%
비정규직/일용직근로자 15
 
15.0%
무직/퇴직 14
 
14.0%
사업자 5
 
5.0%
학생 4
 
4.0%
전업주부 3
 
3.0%

Length

2023-12-10T19:17:57.976081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:58.134961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정규직근로자 59
59.0%
비정규직/일용직근로자 15
 
15.0%
무직/퇴직 14
 
14.0%
사업자 5
 
5.0%
학생 4
 
4.0%
전업주부 3
 
3.0%

dmstc_ecnm_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
38 
약간 부정적
34 
약간 긍정적
16 
매우 부정적
11 
매우 긍정적
 
1

Length

Max length9
Median length6
Mean length7.14
Min length6

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row약간 부정적
2nd row약간 부정적
3rd row비슷함/ 변화없음
4th row약간 긍정적
5th row비슷함/ 변화없음

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 38
38.0%
약간 부정적 34
34.0%
약간 긍정적 16
16.0%
매우 부정적 11
 
11.0%
매우 긍정적 1
 
1.0%

Length

2023-12-10T19:17:58.355478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:58.549206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
약간 50
25.0%
부정적 45
22.5%
비슷함 38
19.0%
변화없음 38
19.0%
긍정적 17
 
8.5%
매우 12
 
6.0%

jb_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
39 
약간 부정적
29 
매우 부정적
17 
약간 긍정적
15 

Length

Max length9
Median length6
Mean length7.17
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row약간 부정적
2nd row매우 부정적
3rd row비슷함/ 변화없음
4th row비슷함/ 변화없음
5th row비슷함/ 변화없음

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 39
39.0%
약간 부정적 29
29.0%
매우 부정적 17
17.0%
약간 긍정적 15
 
15.0%

Length

2023-12-10T19:17:59.014036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:59.150128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부정적 46
23.0%
약간 44
22.0%
비슷함 39
19.5%
변화없음 39
19.5%
매우 17
 
8.5%
긍정적 15
 
7.5%

prices_future_prspect_value
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
약간 부정적
40 
비슷함/ 변화없음
25 
매우 부정적
23 
약간 긍정적
12 

Length

Max length9
Median length6
Mean length6.75
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row매우 부정적
2nd row약간 부정적
3rd row비슷함/ 변화없음
4th row약간 긍정적
5th row약간 부정적

Common Values

ValueCountFrequency (%)
약간 부정적 40
40.0%
비슷함/ 변화없음 25
25.0%
매우 부정적 23
23.0%
약간 긍정적 12
 
12.0%

Length

2023-12-10T19:17:59.283846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:59.433055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부정적 63
31.5%
약간 52
26.0%
비슷함 25
 
12.5%
변화없음 25
 
12.5%
매우 23
 
11.5%
긍정적 12
 
6.0%

stdolv_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
38 
약간 부정적
36 
매우 부정적
14 
약간 긍정적
11 
매우 긍정적
 
1

Length

Max length9
Median length6
Mean length7.14
Min length6

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row약간 부정적
2nd row약간 부정적
3rd row비슷함/ 변화없음
4th row매우 긍정적
5th row약간 부정적

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 38
38.0%
약간 부정적 36
36.0%
매우 부정적 14
 
14.0%
약간 긍정적 11
 
11.0%
매우 긍정적 1
 
1.0%

Length

2023-12-10T19:17:59.595775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:59.791257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부정적 50
25.0%
약간 47
23.5%
비슷함 38
19.0%
변화없음 38
19.0%
매우 15
 
7.5%
긍정적 12
 
6.0%

income_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
43 
약간 부정적
28 
매우 부정적
16 
약간 긍정적
13 

Length

Max length9
Median length6
Mean length7.29
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row약간 부정적
2nd row매우 부정적
3rd row약간 부정적
4th row약간 긍정적
5th row비슷함/ 변화없음

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 43
43.0%
약간 부정적 28
28.0%
매우 부정적 16
 
16.0%
약간 긍정적 13
 
13.0%

Length

2023-12-10T19:17:59.968206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:00.140515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부정적 44
22.0%
비슷함 43
21.5%
변화없음 43
21.5%
약간 41
20.5%
매우 16
 
8.0%
긍정적 13
 
6.5%

spnd_expndtr_rmnpw_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
38 
약간 부정적
37 
매우 부정적
16 
약간 긍정적
9 

Length

Max length9
Median length6
Mean length7.14
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row약간 부정적
2nd row약간 부정적
3rd row약간 부정적
4th row비슷함/ 변화없음
5th row비슷함/ 변화없음

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 38
38.0%
약간 부정적 37
37.0%
매우 부정적 16
16.0%
약간 긍정적 9
 
9.0%

Length

2023-12-10T19:18:00.332097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:00.550253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부정적 53
26.5%
약간 46
23.0%
비슷함 38
19.0%
변화없음 38
19.0%
매우 16
 
8.0%
긍정적 9
 
4.5%

svings_rmnpw_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
36 
약간 부정적
32 
매우 부정적
21 
약간 긍정적
11 

Length

Max length9
Median length6
Mean length7.08
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row매우 부정적
2nd row약간 부정적
3rd row약간 부정적
4th row약간 부정적
5th row비슷함/ 변화없음

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 36
36.0%
약간 부정적 32
32.0%
매우 부정적 21
21.0%
약간 긍정적 11
 
11.0%

Length

2023-12-10T19:18:00.721412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:00.874392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부정적 53
26.5%
약간 43
21.5%
비슷함 36
18.0%
변화없음 36
18.0%
매우 21
 
10.5%
긍정적 11
 
5.5%

debt_scale_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
43 
약간 부정적
30 
매우 부정적
18 
약간 긍정적
9 

Length

Max length9
Median length6
Mean length7.29
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row약간 부정적
2nd row매우 부정적
3rd row비슷함/ 변화없음
4th row비슷함/ 변화없음
5th row비슷함/ 변화없음

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 43
43.0%
약간 부정적 30
30.0%
매우 부정적 18
18.0%
약간 긍정적 9
 
9.0%

Length

2023-12-10T19:18:01.030755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:01.197057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부정적 48
24.0%
비슷함 43
21.5%
변화없음 43
21.5%
약간 39
19.5%
매우 18
 
9.0%
긍정적 9
 
4.5%

Interactions

2023-12-10T19:17:55.137916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:18:01.335990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmlabor_empmn_stle_nmdmstc_ecnm_future_prspect_valuejb_future_prspect_valueprices_future_prspect_valuestdolv_future_prspect_valueincome_future_prspect_valuespnd_expndtr_rmnpw_future_prspect_valuesvings_rmnpw_future_prspect_valuedebt_scale_future_prspect_value
respond_id1.0000.1380.5370.0000.0740.0000.0000.0000.0000.2340.0000.0000.0000.095
sexdstn_flag_cd0.1381.0000.2260.0000.0000.1930.0000.0000.0000.0000.0980.1720.0900.132
agrde_flag_nm0.5370.2261.0000.2060.1860.2660.3920.2400.1150.0860.1450.1030.0000.000
answrr_oc_area_nm0.0000.0000.2061.0000.1960.2390.0000.1360.1060.1570.0000.0000.0000.000
hshld_income_dgree_nm0.0740.0000.1860.1961.0000.5060.0000.1320.2040.0000.2530.1270.1520.226
labor_empmn_stle_nm0.0000.1930.2660.2390.5061.0000.0000.0000.2700.0000.2480.2420.2520.244
dmstc_ecnm_future_prspect_value0.0000.0000.3920.0000.0000.0001.0000.7040.5430.8480.6180.5880.5240.529
jb_future_prspect_value0.0000.0000.2400.1360.1320.0000.7041.0000.7620.5280.8130.7770.6840.736
prices_future_prspect_value0.0000.0000.1150.1060.2040.2700.5430.7621.0000.5170.7300.7700.7120.721
stdolv_future_prspect_value0.2340.0000.0860.1570.0000.0000.8480.5280.5171.0000.6400.7170.6350.541
income_future_prspect_value0.0000.0980.1450.0000.2530.2480.6180.8130.7300.6401.0000.9420.8830.880
spnd_expndtr_rmnpw_future_prspect_value0.0000.1720.1030.0000.1270.2420.5880.7770.7700.7170.9421.0000.9310.843
svings_rmnpw_future_prspect_value0.0000.0900.0000.0000.1520.2520.5240.6840.7120.6350.8830.9311.0000.880
debt_scale_future_prspect_value0.0950.1320.0000.0000.2260.2440.5290.7360.7210.5410.8800.8430.8801.000
2023-12-10T19:18:01.732762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
agrde_flag_nmdmstc_ecnm_future_prspect_valuestdolv_future_prspect_valuehshld_income_dgree_nmsvings_rmnpw_future_prspect_valuedebt_scale_future_prspect_valueanswrr_oc_area_nmjb_future_prspect_valueincome_future_prspect_valuespnd_expndtr_rmnpw_future_prspect_valuesexdstn_flag_cdprices_future_prspect_valuelabor_empmn_stle_nm
agrde_flag_nm1.0000.1540.0250.1500.0000.0000.0920.1960.1160.0810.2720.0910.181
dmstc_ecnm_future_prspect_value0.1541.0000.4840.0000.4490.4540.0000.6370.5430.5120.0000.4670.000
stdolv_future_prspect_value0.0250.4841.0000.0000.5610.4650.0640.4530.5670.6520.0000.4420.000
hshld_income_dgree_nm0.1500.0000.0001.0000.0580.0890.0940.0500.1000.0480.0000.0800.346
svings_rmnpw_future_prspect_value0.0000.4490.5610.0581.0000.5500.0000.3290.5560.6520.0560.3530.161
debt_scale_future_prspect_value0.0000.4540.4650.0890.5501.0000.0000.3740.5500.4950.0850.3600.156
answrr_oc_area_nm0.0920.0000.0640.0940.0000.0001.0000.0570.0000.0000.0000.0370.099
jb_future_prspect_value0.1960.6370.4530.0500.3290.3740.0571.0000.4560.4150.0000.3990.000
income_future_prspect_value0.1160.5430.5670.1000.5560.5500.0000.4561.0000.6780.0620.3680.159
spnd_expndtr_rmnpw_future_prspect_value0.0810.5120.6520.0480.6520.4950.0000.4150.6781.0000.1120.4070.155
sexdstn_flag_cd0.2720.0000.0000.0000.0560.0850.0000.0000.0620.1121.0000.0000.134
prices_future_prspect_value0.0910.4670.4420.0800.3530.3600.0370.3990.3680.4070.0001.0000.174
labor_empmn_stle_nm0.1810.0000.0000.3460.1610.1560.0990.0000.1590.1550.1340.1741.000
2023-12-10T19:18:02.017937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmlabor_empmn_stle_nmdmstc_ecnm_future_prspect_valuejb_future_prspect_valueprices_future_prspect_valuestdolv_future_prspect_valueincome_future_prspect_valuespnd_expndtr_rmnpw_future_prspect_valuesvings_rmnpw_future_prspect_valuedebt_scale_future_prspect_value
respond_id1.0000.1700.2210.0000.0570.0000.0000.0000.0000.0750.0300.0000.0000.072
sexdstn_flag_cd0.1701.0000.2720.0000.0000.1340.0000.0000.0000.0000.0620.1120.0560.085
agrde_flag_nm0.2210.2721.0000.0920.1500.1810.1540.1960.0910.0250.1160.0810.0000.000
answrr_oc_area_nm0.0000.0000.0921.0000.0940.0990.0000.0570.0370.0640.0000.0000.0000.000
hshld_income_dgree_nm0.0570.0000.1500.0941.0000.3460.0000.0500.0800.0000.1000.0480.0580.089
labor_empmn_stle_nm0.0000.1340.1810.0990.3461.0000.0000.0000.1740.0000.1590.1550.1610.156
dmstc_ecnm_future_prspect_value0.0000.0000.1540.0000.0000.0001.0000.6370.4670.4840.5430.5120.4490.454
jb_future_prspect_value0.0000.0000.1960.0570.0500.0000.6371.0000.3990.4530.4560.4150.3290.374
prices_future_prspect_value0.0000.0000.0910.0370.0800.1740.4670.3991.0000.4420.3680.4070.3530.360
stdolv_future_prspect_value0.0750.0000.0250.0640.0000.0000.4840.4530.4421.0000.5670.6520.5610.465
income_future_prspect_value0.0300.0620.1160.0000.1000.1590.5430.4560.3680.5671.0000.6780.5560.550
spnd_expndtr_rmnpw_future_prspect_value0.0000.1120.0810.0000.0480.1550.5120.4150.4070.6520.6781.0000.6520.495
svings_rmnpw_future_prspect_value0.0000.0560.0000.0000.0580.1610.4490.3290.3530.5610.5560.6521.0000.550
debt_scale_future_prspect_value0.0720.0850.0000.0000.0890.1560.4540.3740.3600.4650.5500.4950.5501.000

Missing values

2023-12-10T19:17:55.364584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:17:55.683558image/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_nmlabor_empmn_stle_nmdmstc_ecnm_future_prspect_valuejb_future_prspect_valueprices_future_prspect_valuestdolv_future_prspect_valueincome_future_prspect_valuespnd_expndtr_rmnpw_future_prspect_valuesvings_rmnpw_future_prspect_valuedebt_scale_future_prspect_value
0406520211103M30대부산광역시400만원초과700만원이하사업자약간 부정적약간 부정적매우 부정적약간 부정적약간 부정적약간 부정적매우 부정적약간 부정적
142049420211103F20대대전광역시모름/무응답전업주부약간 부정적매우 부정적약간 부정적약간 부정적매우 부정적약간 부정적약간 부정적매우 부정적
2935720211103F60대서울특별시200만원이하전업주부비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음약간 부정적약간 부정적약간 부정적비슷함/ 변화없음
31285620211103M40대서울특별시200만원초과400만원이하정규직근로자약간 긍정적비슷함/ 변화없음약간 긍정적매우 긍정적약간 긍정적비슷함/ 변화없음약간 부정적비슷함/ 변화없음
41832820211103M30대경기도200만원초과400만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음약간 부정적약간 부정적비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음
52761820211103M50대대전광역시200만원이하정규직근로자비슷함/ 변화없음약간 부정적약간 부정적비슷함/ 변화없음약간 부정적약간 부정적약간 부정적비슷함/ 변화없음
63069420211103F30대서울특별시200만원이하정규직근로자약간 부정적약간 부정적약간 부정적약간 부정적약간 부정적약간 부정적매우 부정적약간 부정적
736567320211103M20대서울특별시200만원이하무직/퇴직매우 부정적매우 부정적매우 부정적매우 부정적매우 부정적매우 부정적매우 부정적매우 부정적
83761920211103F60대인천광역시400만원초과700만원이하정규직근로자비슷함/ 변화없음약간 부정적약간 긍정적비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음약간 부정적
94779220211103M40대부산광역시모름/무응답정규직근로자비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음
respond_idexamin_begin_desexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmlabor_empmn_stle_nmdmstc_ecnm_future_prspect_valuejb_future_prspect_valueprices_future_prspect_valuestdolv_future_prspect_valueincome_future_prspect_valuespnd_expndtr_rmnpw_future_prspect_valuesvings_rmnpw_future_prspect_valuedebt_scale_future_prspect_value
9044269020211103M20대대구광역시200만원초과400만원이하정규직근로자약간 긍정적비슷함/ 변화없음약간 긍정적비슷함/ 변화없음약간 긍정적약간 긍정적약간 긍정적약간 긍정적
9144308620211103M20대경기도200만원이하정규직근로자약간 부정적약간 부정적약간 부정적약간 부정적매우 부정적매우 부정적매우 부정적약간 부정적
9244356220211103F20대대전광역시모름/무응답무직/퇴직비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음
9344414520211103F20대경기도200만원이하정규직근로자비슷함/ 변화없음약간 부정적매우 부정적약간 부정적비슷함/ 변화없음비슷함/ 변화없음약간 부정적매우 부정적
9444463820211103F20대경상북도모름/무응답비정규직/일용직근로자약간 긍정적약간 긍정적약간 긍정적약간 긍정적약간 긍정적약간 긍정적약간 긍정적약간 긍정적
9544464320211103M20대대구광역시모름/무응답학생매우 부정적매우 부정적매우 부정적약간 부정적매우 부정적매우 부정적약간 부정적매우 부정적
9644478920211103M20대서울특별시200만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음비슷함/ 변화없음약간 긍정적약간 긍정적비슷함/ 변화없음약간 긍정적약간 긍정적
97103479120211103F30대서울특별시200만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음약간 부정적매우 부정적매우 부정적매우 부정적매우 부정적매우 부정적
98108157820211103F30대서울특별시200만원초과400만원이하정규직근로자매우 부정적매우 부정적약간 부정적매우 부정적약간 부정적약간 부정적약간 부정적매우 부정적
99114680220211103F30대경기도200만원초과400만원이하정규직근로자약간 부정적비슷함/ 변화없음매우 부정적약간 부정적비슷함/ 변화없음약간 부정적약간 부정적비슷함/ 변화없음