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_ym has constant value ""Constant
respond_id has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:57:49.337299
Analysis finished2023-12-10 09:57:51.290330
Duration1.95 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%
Mean53338360
Minimum53322284
Maximum53377385
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:51.420861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53322284
5-th percentile53324217
Q153329630
median53338697
Q353345541
95-th percentile53349995
Maximum53377385
Range55101
Interquartile range (IQR)15911.5

Descriptive statistics

Standard deviation10723.986
Coefficient of variation (CV)0.00020105578
Kurtosis3.2422755
Mean53338360
Median Absolute Deviation (MAD)7639
Skewness1.2260123
Sum5.333836 × 109
Variance1.1500387 × 108
MonotonicityNot monotonic
2023-12-10T18:57:51.638001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53322284 1
 
1.0%
53340557 1
 
1.0%
53343579 1
 
1.0%
53343549 1
 
1.0%
53341882 1
 
1.0%
53341707 1
 
1.0%
53341190 1
 
1.0%
53341180 1
 
1.0%
53341087 1
 
1.0%
53341078 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
53322284 1
1.0%
53323279 1
1.0%
53323334 1
1.0%
53323480 1
1.0%
53324157 1
1.0%
53324220 1
1.0%
53324365 1
1.0%
53324459 1
1.0%
53324765 1
1.0%
53325138 1
1.0%
ValueCountFrequency (%)
53377385 1
1.0%
53377223 1
1.0%
53377200 1
1.0%
53350836 1
1.0%
53350746 1
1.0%
53349955 1
1.0%
53349856 1
1.0%
53349828 1
1.0%
53349404 1
1.0%
53349132 1
1.0%

examin_ym
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
202204
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202204
2nd row202204
3rd row202204
4th row202204
5th row202204

Common Values

ValueCountFrequency (%)
202204 100
100.0%

Length

2023-12-10T18:57:51.849292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:52.000027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202204 100
100.0%

sexdstn_flag_cd
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M
67 
F
33 

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 (%)
M 67
67.0%
F 33
33.0%

Length

2023-12-10T18:57:52.173134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:52.349636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 67
67.0%
f 33
33.0%

agrde_flag_nm
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
50대
24 
20대
21 
40대
20 
30대
18 
60대
17 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50대
2nd row30대
3rd row50대
4th row40대
5th row20대

Common Values

ValueCountFrequency (%)
50대 24
24.0%
20대 21
21.0%
40대 20
20.0%
30대 18
18.0%
60대 17
17.0%

Length

2023-12-10T18:57:52.553124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:52.740032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50대 24
24.0%
20대 21
21.0%
40대 20
20.0%
30대 18
18.0%
60대 17
17.0%

answrr_oc_area_nm
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
23 
경기도
23 
부산광역시
9 
경상북도
8 
충청남도
6 
Other values (11)
31 

Length

Max length7
Median length5
Mean length4.3
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 23
23.0%
경기도 23
23.0%
부산광역시 9
 
9.0%
경상북도 8
 
8.0%
충청남도 6
 
6.0%
경상남도 6
 
6.0%
대구광역시 5
 
5.0%
대전광역시 4
 
4.0%
울산광역시 3
 
3.0%
광주광역시 3
 
3.0%
Other values (6) 10
10.0%

Length

2023-12-10T18:57:52.993767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 23
23.0%
경기도 23
23.0%
부산광역시 9
 
9.0%
경상북도 8
 
8.0%
충청남도 6
 
6.0%
경상남도 6
 
6.0%
대구광역시 5
 
5.0%
대전광역시 4
 
4.0%
울산광역시 3
 
3.0%
광주광역시 3
 
3.0%
Other values (6) 10
10.0%

hshld_income_dgree_nm
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
300만원 미만
28 
300이상500만원 미만
25 
500이상700만원 미만
21 
700만원 이상
16 
무응답
10 

Length

Max length13
Median length8
Mean length9.8
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
300만원 미만 28
28.0%
300이상500만원 미만 25
25.0%
500이상700만원 미만 21
21.0%
700만원 이상 16
16.0%
무응답 10
 
10.0%

Length

2023-12-10T18:57:53.248905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:53.495754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 74
38.9%
300만원 28
 
14.7%
300이상500만원 25
 
13.2%
500이상700만원 21
 
11.1%
700만원 16
 
8.4%
이상 16
 
8.4%
무응답 10
 
5.3%

sports_viewng_item_rn1_value
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
축구
33 
야구
26 
골프
8 
e스포츠(게임)
8 
배구
7 
Other values (4)
18 

Length

Max length8
Median length2
Mean length2.94
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row복싱-격투기
2nd row축구
3rd row야구
4th row축구
5th row야구

Common Values

ValueCountFrequency (%)
축구 33
33.0%
야구 26
26.0%
골프 8
 
8.0%
e스포츠(게임) 8
 
8.0%
배구 7
 
7.0%
농구 6
 
6.0%
테니스-배드민턴 5
 
5.0%
복싱-격투기 4
 
4.0%
기타 3
 
3.0%

Length

2023-12-10T18:57:53.878042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:54.266364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축구 33
33.0%
야구 26
26.0%
골프 8
 
8.0%
e스포츠(게임 8
 
8.0%
배구 7
 
7.0%
농구 6
 
6.0%
테니스-배드민턴 5
 
5.0%
복싱-격투기 4
 
4.0%
기타 3
 
3.0%

sports_viewng_item_rn2_value
Categorical

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
없음
23 
축구
21 
야구
20 
배구
14 
골프
9 
Other values (3)
13 

Length

Max length8
Median length2
Mean length2.32
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row야구
2nd row골프
3rd row골프
4th row없음
5th row배구

Common Values

ValueCountFrequency (%)
없음 23
23.0%
축구 21
21.0%
야구 20
20.0%
배구 14
14.0%
골프 9
 
9.0%
농구 7
 
7.0%
e스포츠(게임) 4
 
4.0%
복싱-격투기 2
 
2.0%

Length

2023-12-10T18:57:54.521026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:54.750157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
없음 23
23.0%
축구 21
21.0%
야구 20
20.0%
배구 14
14.0%
골프 9
 
9.0%
농구 7
 
7.0%
e스포츠(게임 4
 
4.0%
복싱-격투기 2
 
2.0%

sports_viewng_item_rn3_value
Categorical

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
없음
50 
배구
12 
축구
9 
농구
7 
야구
7 
Other values (5)
15 

Length

Max length8
Median length2
Mean length2.46
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row농구
2nd row없음
3rd row축구
4th row없음
5th row없음

Common Values

ValueCountFrequency (%)
없음 50
50.0%
배구 12
 
12.0%
축구 9
 
9.0%
농구 7
 
7.0%
야구 7
 
7.0%
복싱-격투기 4
 
4.0%
골프 4
 
4.0%
테니스-배드민턴 4
 
4.0%
기타 2
 
2.0%
e스포츠(게임) 1
 
1.0%

Length

2023-12-10T18:57:55.027481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:55.302141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
없음 50
50.0%
배구 12
 
12.0%
축구 9
 
9.0%
농구 7
 
7.0%
야구 7
 
7.0%
복싱-격투기 4
 
4.0%
골프 4
 
4.0%
테니스-배드민턴 4
 
4.0%
기타 2
 
2.0%
e스포츠(게임 1
 
1.0%

Interactions

2023-12-10T18:57:50.267014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:57:55.521989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmsports_viewng_item_rn1_valuesports_viewng_item_rn2_valuesports_viewng_item_rn3_value
respond_id1.0000.0000.1380.3710.2090.1550.0000.000
sexdstn_flag_cd0.0001.0000.0000.0000.1210.1770.1910.000
agrde_flag_nm0.1380.0001.0000.1260.5550.2490.2250.591
answrr_oc_area_nm0.3710.0000.1261.0000.0000.2440.6600.000
hshld_income_dgree_nm0.2090.1210.5550.0001.0000.1640.2150.407
sports_viewng_item_rn1_value0.1550.1770.2490.2440.1641.0000.3910.000
sports_viewng_item_rn2_value0.0000.1910.2250.6600.2150.3911.0000.554
sports_viewng_item_rn3_value0.0000.0000.5910.0000.4070.0000.5541.000
2023-12-10T18:57:56.054348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
hshld_income_dgree_nmsports_viewng_item_rn1_valuesports_viewng_item_rn3_valuesports_viewng_item_rn2_valuesexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nm
hshld_income_dgree_nm1.0000.0890.1730.1280.1440.2340.000
sports_viewng_item_rn1_value0.0891.0000.0000.2000.1680.1400.090
sports_viewng_item_rn3_value0.1730.0001.0000.2990.0000.2760.000
sports_viewng_item_rn2_value0.1280.2000.2991.0000.1360.1350.277
sexdstn_flag_cd0.1440.1680.0000.1361.0000.0000.000
agrde_flag_nm0.2340.1400.2760.1350.0001.0000.046
answrr_oc_area_nm0.0000.0900.0000.2770.0000.0461.000
2023-12-10T18:57:56.532122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
respond_idsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmsports_viewng_item_rn1_valuesports_viewng_item_rn2_valuesports_viewng_item_rn3_value
respond_id1.0000.0000.1010.1780.1300.0340.0000.000
sexdstn_flag_cd0.0001.0000.0000.0000.1440.1680.1360.000
agrde_flag_nm0.1010.0001.0000.0460.2340.1400.1350.276
answrr_oc_area_nm0.1780.0000.0461.0000.0000.0900.2770.000
hshld_income_dgree_nm0.1300.1440.2340.0001.0000.0890.1280.173
sports_viewng_item_rn1_value0.0340.1680.1400.0900.0891.0000.2000.000
sports_viewng_item_rn2_value0.0000.1360.1350.2770.1280.2001.0000.299
sports_viewng_item_rn3_value0.0000.0000.2760.0000.1730.0000.2991.000

Missing values

2023-12-10T18:57:50.529178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:57:51.179469image/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_ymsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmsports_viewng_item_rn1_valuesports_viewng_item_rn2_valuesports_viewng_item_rn3_value
053322284202204M50대서울특별시300이상500만원 미만복싱-격투기야구농구
153377200202204F30대울산광역시무응답축구골프없음
253323279202204F50대서울특별시700만원 이상야구골프축구
353323334202204M40대서울특별시500이상700만원 미만축구없음없음
453323480202204M20대서울특별시700만원 이상야구배구없음
553324157202204M60대서울특별시300만원 미만배구농구복싱-격투기
653324220202204M50대서울특별시300이상500만원 미만축구야구기타
753377223202204F30대인천광역시500이상700만원 미만축구없음없음
853324365202204F40대서울특별시300만원 미만기타없음없음
953324459202204M30대서울특별시300만원 미만테니스-배드민턴없음없음
respond_idexamin_ymsexdstn_flag_cdagrde_flag_nmanswrr_oc_area_nmhshld_income_dgree_nmsports_viewng_item_rn1_valuesports_viewng_item_rn2_valuesports_viewng_item_rn3_value
9053348390202204M60대부산광역시300만원 미만축구야구배구
9153349005202204M50대서울특별시500이상700만원 미만야구없음없음
9253349115202204F20대충청남도무응답축구없음없음
9353349132202204M60대전라북도300만원 미만축구배구없음
9453349404202204M50대광주광역시300이상500만원 미만축구야구배구
9553349828202204F60대서울특별시300이상500만원 미만골프축구야구
9653349856202204M30대서울특별시무응답e스포츠(게임)없음없음
9753349955202204M60대경상남도300이상500만원 미만야구골프테니스-배드민턴
9853350746202204M20대대구광역시무응답야구없음없음
9953350836202204M20대경기도300이상500만원 미만복싱-격투기축구없음