Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory75.3 B

Variable types

Numeric1
Categorical8

Alerts

examin_begin_de has constant value ""Constant
qlolf_vartion_evl_value is highly overall correlated with qlolf_future_prspect_valueHigh correlation
qlolf_future_prspect_value is highly overall correlated with qlolf_vartion_evl_valueHigh correlation
respond_id has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:58:27.050270
Analysis finished2023-12-10 09:58:28.822789
Duration1.77 second
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
2023-12-10T18:58:28.964100image/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
2023-12-10T18:58:29.288574image/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

2023-12-10T18:58:29.540889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:29.713352image/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

2023-12-10T18:58:29.892446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:30.075715image/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

2023-12-10T18:58:30.294173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:30.514766image/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

2023-12-10T18:58:30.857224image/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

2023-12-10T18:58:31.173816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:31.448044image/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

2023-12-10T18:58:31.712898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:31.981616image/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%

qlolf_vartion_evl_value
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
55 
약간 부정적
27 
매우 부정적
15 
약간 긍정적
 
3

Length

Max length9
Median length9
Mean length7.65
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 55
55.0%
약간 부정적 27
27.0%
매우 부정적 15
 
15.0%
약간 긍정적 3
 
3.0%

Length

2023-12-10T18:58:32.318009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:32.571929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비슷함 55
27.5%
변화없음 55
27.5%
부정적 42
21.0%
약간 30
15.0%
매우 15
 
7.5%
긍정적 3
 
1.5%

qlolf_future_prspect_value
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
비슷함/ 변화없음
49 
약간 부정적
27 
매우 부정적
12 
약간 긍정적
10 
매우 긍정적
 
2

Length

Max length9
Median length6
Mean length7.47
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비슷함/ 변화없음 49
49.0%
약간 부정적 27
27.0%
매우 부정적 12
 
12.0%
약간 긍정적 10
 
10.0%
매우 긍정적 2
 
2.0%

Length

2023-12-10T18:58:33.040709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:33.314344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비슷함 49
24.5%
변화없음 49
24.5%
부정적 39
19.5%
약간 37
18.5%
매우 14
 
7.0%
긍정적 12
 
6.0%

Interactions

2023-12-10T18:58:27.968972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:58:33.481262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmlabor_empmn_stle_nmqlolf_vartion_evl_valueqlolf_future_prspect_value
respond_id1.0000.1380.5370.0000.0740.0000.0530.000
sexdstn_flag_cd0.1381.0000.2260.0000.0000.1930.0000.000
agrde_flag_nm0.5370.2261.0000.2060.1860.2660.0810.043
answrr_oc_area_nm0.0000.0000.2061.0000.1960.2390.3030.681
hshld_income_dgree_nm0.0740.0000.1860.1961.0000.5060.2780.000
labor_empmn_stle_nm0.0000.1930.2660.2390.5061.0000.3360.336
qlolf_vartion_evl_value0.0530.0000.0810.3030.2780.3361.0000.661
qlolf_future_prspect_value0.0000.0000.0430.6810.0000.3360.6611.000
2023-12-10T18:58:33.809680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
agrde_flag_nmsexdstn_flag_cdhshld_income_dgree_nmlabor_empmn_stle_nmqlolf_future_prspect_valueanswrr_oc_area_nmqlolf_vartion_evl_value
agrde_flag_nm1.0000.2720.1500.1810.0000.0920.062
sexdstn_flag_cd0.2721.0000.0000.1340.0000.0000.000
hshld_income_dgree_nm0.1500.0001.0000.3460.0000.0940.111
labor_empmn_stle_nm0.1810.1340.3461.0000.2330.0990.219
qlolf_future_prspect_value0.0000.0000.0000.2331.0000.4050.589
answrr_oc_area_nm0.0920.0000.0940.0990.4051.0000.155
qlolf_vartion_evl_value0.0620.0000.1110.2190.5890.1551.000
2023-12-10T18:58:34.063936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmlabor_empmn_stle_nmqlolf_vartion_evl_valueqlolf_future_prspect_value
respond_id1.0000.1700.2210.0000.0570.0000.0000.000
sexdstn_flag_cd0.1701.0000.2720.0000.0000.1340.0000.000
agrde_flag_nm0.2210.2721.0000.0920.1500.1810.0620.000
answrr_oc_area_nm0.0000.0000.0921.0000.0940.0990.1550.405
hshld_income_dgree_nm0.0570.0000.1500.0941.0000.3460.1110.000
labor_empmn_stle_nm0.0000.1340.1810.0990.3461.0000.2190.233
qlolf_vartion_evl_value0.0000.0000.0620.1550.1110.2191.0000.589
qlolf_future_prspect_value0.0000.0000.0000.4050.0000.2330.5891.000

Missing values

2023-12-10T18:58:28.428178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:58:28.715773image/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_nmqlolf_vartion_evl_valueqlolf_future_prspect_value
0406520211103M30대부산광역시400만원초과700만원이하사업자매우 부정적약간 부정적
142049420211103F20대대전광역시모름/무응답전업주부약간 부정적매우 부정적
2935720211103F60대서울특별시200만원이하전업주부비슷함/ 변화없음약간 부정적
31285620211103M40대서울특별시200만원초과400만원이하정규직근로자비슷함/ 변화없음약간 부정적
41832820211103M30대경기도200만원초과400만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음
52761820211103M50대대전광역시200만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음
63069420211103F30대서울특별시200만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음
736567320211103M20대서울특별시200만원이하무직/퇴직매우 부정적약간 부정적
83761920211103F60대인천광역시400만원초과700만원이하정규직근로자약간 부정적비슷함/ 변화없음
94779220211103M40대부산광역시모름/무응답정규직근로자비슷함/ 변화없음비슷함/ 변화없음
respond_idexamin_begin_desexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmlabor_empmn_stle_nmqlolf_vartion_evl_valueqlolf_future_prspect_value
9044269020211103M20대대구광역시200만원초과400만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음
9144308620211103M20대경기도200만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음
9244356220211103F20대대전광역시모름/무응답무직/퇴직비슷함/ 변화없음비슷함/ 변화없음
9344414520211103F20대경기도200만원이하정규직근로자약간 부정적약간 부정적
9444463820211103F20대경상북도모름/무응답비정규직/일용직근로자약간 긍정적약간 긍정적
9544464320211103M20대대구광역시모름/무응답학생매우 부정적매우 부정적
9644478920211103M20대서울특별시200만원이하정규직근로자비슷함/ 변화없음약간 긍정적
97103479120211103F30대서울특별시200만원이하정규직근로자매우 부정적약간 부정적
98108157820211103F30대서울특별시200만원초과400만원이하정규직근로자약간 부정적약간 부정적
99114680220211103F30대경기도200만원초과400만원이하정규직근로자비슷함/ 변화없음비슷함/ 변화없음