Overview

Dataset statistics

Number of variables26
Number of observations500
Missing cells3639
Missing cells (%)28.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory114.4 KiB
Average record size in memory234.3 B

Variable types

Numeric16
Categorical10

Dataset

Description샘플 데이터
Author서울시
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=25

Alerts

법인구분(josic_c) is highly imbalanced (57.0%)Imbalance
월(chang_m) is highly imbalanced (74.0%)Imbalance
자영업자_합계(emp_ja) is highly imbalanced (50.4%)Imbalance
무급가족종사자_남자수(emp_mu_m) is highly imbalanced (76.6%)Imbalance
무급가족종사자_여자수(emp_mu_f) is highly imbalanced (71.3%)Imbalance
무급가족종사자_합계(emp_mu) is highly imbalanced (71.5%)Imbalance
무급(기타)종사자_여자(emp_mo_m) is highly imbalanced (95.0%)Imbalance
대표자연령(출생연도)(d_age) has 71 (14.2%) missing valuesMissing
상용종사자_남자(emp_sa_m) has 351 (70.2%) missing valuesMissing
상용종사자_여자(emp_sa_f) has 341 (68.2%) missing valuesMissing
상용종사자_합계(emp_sa) has 286 (57.2%) missing valuesMissing
임시일용종사자_남자(emp_im_m) has 464 (92.8%) missing valuesMissing
임시일용종사자_여자(emp_im_f) has 434 (86.8%) missing valuesMissing
임시일용종사자_합계(emp_im) has 427 (85.4%) missing valuesMissing
무급(기타)종사자_남자(emp_mo_m) has 491 (98.2%) missing valuesMissing
무급(기타)종사자_합계(emp_mo) has 483 (96.6%) missing valuesMissing
종사자_남자계(emp_to_m) has 116 (23.2%) missing valuesMissing
종사자_여자계(emp_to_f) has 175 (35.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 14:49:37.675584
Analysis finished2023-12-10 14:49:37.935807
Duration0.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

한국행정구역분류(zone_c)
Real number (ℝ)

Distinct243
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1113828.3
Minimum1101053
Maximum1125074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:38.060762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1101053
5-th percentile1101068.9
Q11106084.5
median1115063
Q31122051
95-th percentile1124063
Maximum1125074
Range24021
Interquartile range (IQR)15966.5

Descriptive statistics

Standard deviation7980.3493
Coefficient of variation (CV)0.0071647932
Kurtosis-1.3710365
Mean1113828.3
Median Absolute Deviation (MAD)7001
Skewness-0.26328943
Sum5.5691414 × 108
Variance63685975
MonotonicityNot monotonic
2023-12-10T23:49:38.393250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1101061 10
 
2.0%
1102054 8
 
1.6%
1104068 7
 
1.4%
1119076 7
 
1.4%
1123064 7
 
1.4%
1103073 6
 
1.2%
1118051 6
 
1.2%
1122067 6
 
1.2%
1117067 6
 
1.2%
1102059 6
 
1.2%
Other values (233) 431
86.2%
ValueCountFrequency (%)
1101053 5
1.0%
1101060 1
 
0.2%
1101061 10
2.0%
1101063 6
1.2%
1101067 2
 
0.4%
1101068 1
 
0.2%
1101069 1
 
0.2%
1101071 2
 
0.4%
1101072 2
 
0.4%
1101073 3
 
0.6%
ValueCountFrequency (%)
1125074 2
0.4%
1125072 2
0.4%
1125066 1
0.2%
1125061 1
0.2%
1125056 1
0.2%
1125055 1
0.2%
1125054 1
0.2%
1125053 2
0.4%
1124080 1
0.2%
1124077 1
0.2%

성별(d_sex)
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
334 
2
166 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 334
66.8%
2 166
33.2%

Length

2023-12-10T23:49:38.551091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:38.697488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 334
66.8%
2 166
33.2%

대표자연령(출생연도)(d_age)
Real number (ℝ)

MISSING 

Distinct53
Distinct (%)12.4%
Missing71
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean1961.2494
Minimum1928
Maximum1991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:38.825603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1928
5-th percentile1945
Q11954
median1961
Q31969
95-th percentile1978.6
Maximum1991
Range63
Interquartile range (IQR)15

Descriptive statistics

Standard deviation10.441684
Coefficient of variation (CV)0.005323996
Kurtosis-0.29695112
Mean1961.2494
Median Absolute Deviation (MAD)8
Skewness-0.038546365
Sum841376
Variance109.02877
MonotonicityNot monotonic
2023-12-10T23:49:38.966916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1958 21
 
4.2%
1956 20
 
4.0%
1964 19
 
3.8%
1959 18
 
3.6%
1962 18
 
3.6%
1968 16
 
3.2%
1955 15
 
3.0%
1963 14
 
2.8%
1948 13
 
2.6%
1970 13
 
2.6%
Other values (43) 262
52.4%
(Missing) 71
 
14.2%
ValueCountFrequency (%)
1928 1
 
0.2%
1933 1
 
0.2%
1937 2
 
0.4%
1938 1
 
0.2%
1939 3
0.6%
1940 2
 
0.4%
1941 1
 
0.2%
1942 1
 
0.2%
1943 3
0.6%
1944 6
1.2%
ValueCountFrequency (%)
1991 1
 
0.2%
1989 1
 
0.2%
1985 1
 
0.2%
1984 1
 
0.2%
1983 1
 
0.2%
1982 4
0.8%
1981 1
 
0.2%
1980 6
1.2%
1979 6
1.2%
1978 5
1.0%

법인구분(josic_c)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
391 
2
81 
4
 
17
3
 
10
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row4
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 391
78.2%
2 81
 
16.2%
4 17
 
3.4%
3 10
 
2.0%
5 1
 
0.2%

Length

2023-12-10T23:49:39.128250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:39.243455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 391
78.2%
2 81
 
16.2%
4 17
 
3.4%
3 10
 
2.0%
5 1
 
0.2%

사업체구분(kubun_c)
Real number (ℝ)

Distinct40
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2004.564
Minimum1962
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:39.404750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1962
5-th percentile1986
Q12001
median2008
Q32011
95-th percentile2013
Maximum2013
Range51
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.9008063
Coefficient of variation (CV)0.0044402705
Kurtosis2.4007811
Mean2004.564
Median Absolute Deviation (MAD)4
Skewness-1.5296746
Sum1002282
Variance79.224353
MonotonicityNot monotonic
2023-12-10T23:49:39.599805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
2012 61
 
12.2%
2013 61
 
12.2%
2011 42
 
8.4%
2008 32
 
6.4%
2010 29
 
5.8%
2009 26
 
5.2%
2004 23
 
4.6%
2006 22
 
4.4%
2005 20
 
4.0%
2003 20
 
4.0%
Other values (30) 164
32.8%
ValueCountFrequency (%)
1962 1
 
0.2%
1969 2
0.4%
1971 1
 
0.2%
1973 1
 
0.2%
1978 1
 
0.2%
1979 3
0.6%
1980 2
0.4%
1981 1
 
0.2%
1982 1
 
0.2%
1983 2
0.4%
ValueCountFrequency (%)
2013 61
12.2%
2012 61
12.2%
2011 42
8.4%
2010 29
5.8%
2009 26
5.2%
2008 32
6.4%
2007 17
 
3.4%
2006 22
 
4.4%
2005 20
 
4.0%
2004 23
 
4.6%

연도(chang_y)
Real number (ℝ)

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.226
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:39.750705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39.25
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6.25

Descriptive statistics

Standard deviation3.5156284
Coefficient of variation (CV)0.56466888
Kurtosis-1.2562442
Mean6.226
Median Absolute Deviation (MAD)3
Skewness0.13723468
Sum3113
Variance12.359643
MonotonicityNot monotonic
2023-12-10T23:49:39.881325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 56
11.2%
4 51
10.2%
1 51
10.2%
5 46
9.2%
10 46
9.2%
12 40
8.0%
11 39
7.8%
6 36
7.2%
7 35
7.0%
2 34
6.8%
Other values (2) 66
13.2%
ValueCountFrequency (%)
1 51
10.2%
2 34
6.8%
3 56
11.2%
4 51
10.2%
5 46
9.2%
6 36
7.2%
7 35
7.0%
8 32
6.4%
9 34
6.8%
10 46
9.2%
ValueCountFrequency (%)
12 40
8.0%
11 39
7.8%
10 46
9.2%
9 34
6.8%
8 32
6.4%
7 35
7.0%
6 36
7.2%
5 46
9.2%
4 51
10.2%
3 56
11.2%

월(chang_m)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
466 
3
 
26
2
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 466
93.2%
3 26
 
5.2%
2 8
 
1.6%

Length

2023-12-10T23:49:40.011959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:40.130006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 466
93.2%
3 26
 
5.2%
2 8
 
1.6%

한국표준산업분류(snl_b)
Real number (ℝ)

Distinct205
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57314.112
Minimum10742
Maximum96993
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:40.262962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10742
5-th percentile25996.1
Q147127.25
median49312
Q368221
95-th percentile96112
Maximum96993
Range86251
Interquartile range (IQR)21093.75

Descriptive statistics

Standard deviation19571.987
Coefficient of variation (CV)0.34148635
Kurtosis-0.092539505
Mean57314.112
Median Absolute Deviation (MAD)6882
Skewness0.41869512
Sum28657056
Variance3.8306266 × 108
MonotonicityNot monotonic
2023-12-10T23:49:40.434786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49231 41
 
8.2%
56111 26
 
5.2%
49312 22
 
4.4%
68221 17
 
3.4%
56220 14
 
2.8%
47416 11
 
2.2%
96912 9
 
1.8%
56194 9
 
1.8%
42412 8
 
1.6%
96112 8
 
1.6%
Other values (195) 335
67.0%
ValueCountFrequency (%)
10742 1
0.2%
10796 1
0.2%
13222 1
0.2%
14112 1
0.2%
14130 2
0.4%
14191 2
0.4%
14300 2
0.4%
15110 1
0.2%
16221 1
0.2%
17222 1
0.2%
ValueCountFrequency (%)
96993 1
 
0.2%
96992 4
0.8%
96921 1
 
0.2%
96912 9
1.8%
96122 5
1.0%
96119 1
 
0.2%
96112 8
1.6%
96111 1
 
0.2%
95391 1
 
0.2%
95310 1
 
0.2%

자영업자_남자수(emp_ja_m)
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
255 
<NA>
240 
0
 
4
2
 
1

Length

Max length4
Median length1
Mean length2.44
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row<NA>
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 255
51.0%
<NA> 240
48.0%
0 4
 
0.8%
2 1
 
0.2%

Length

2023-12-10T23:49:40.562541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:40.658096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 255
51.0%
na 240
48.0%
0 4
 
0.8%
2 1
 
0.2%

자영업자_여자수(emp_ja_f)
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
359 
1
139 
0
 
2

Length

Max length4
Median length4
Mean length3.154
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 359
71.8%
1 139
 
27.8%
0 2
 
0.4%

Length

2023-12-10T23:49:40.765162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:40.871325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 359
71.8%
1 139
 
27.8%
0 2
 
0.4%

자영업자_합계(emp_ja)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
396 
<NA>
100 
0
 
4

Length

Max length4
Median length1
Mean length1.6
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 396
79.2%
<NA> 100
 
20.0%
0 4
 
0.8%

Length

2023-12-10T23:49:40.970128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:41.054555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 396
79.2%
na 100
 
20.0%
0 4
 
0.8%

무급가족종사자_남자수(emp_mu_m)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
470 
1
 
24
0
 
6

Length

Max length4
Median length4
Mean length3.82
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 470
94.0%
1 24
 
4.8%
0 6
 
1.2%

Length

2023-12-10T23:49:41.147435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:41.236243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 470
94.0%
1 24
 
4.8%
0 6
 
1.2%

무급가족종사자_여자수(emp_mu_f)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
457 
1
 
40
0
 
3

Length

Max length4
Median length4
Mean length3.742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 457
91.4%
1 40
 
8.0%
0 3
 
0.6%

Length

2023-12-10T23:49:41.326455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:41.416073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 457
91.4%
1 40
 
8.0%
0 3
 
0.6%

무급가족종사자_합계(emp_mu)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
433 
1
59 
0
 
4
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.598
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 433
86.6%
1 59
 
11.8%
0 4
 
0.8%
2 3
 
0.6%
3 1
 
0.2%

Length

2023-12-10T23:49:41.519505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:41.629045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 433
86.6%
1 59
 
11.8%
0 4
 
0.8%
2 3
 
0.6%
3 1
 
0.2%

상용종사자_남자(emp_sa_m)
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)14.8%
Missing351
Missing (%)70.2%
Infinite0
Infinite (%)0.0%
Mean5.1275168
Minimum0
Maximum100
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:41.725859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q34
95-th percentile18.8
Maximum100
Range100
Interquartile range (IQR)3

Descriptive statistics

Standard deviation12.091033
Coefficient of variation (CV)2.358068
Kurtosis39.494855
Mean5.1275168
Median Absolute Deviation (MAD)1
Skewness5.855137
Sum764
Variance146.19309
MonotonicityNot monotonic
2023-12-10T23:49:41.828944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 63
 
12.6%
2 24
 
4.8%
3 17
 
3.4%
4 16
 
3.2%
5 5
 
1.0%
6 3
 
0.6%
16 2
 
0.4%
27 2
 
0.4%
9 2
 
0.4%
0 2
 
0.4%
Other values (12) 13
 
2.6%
(Missing) 351
70.2%
ValueCountFrequency (%)
0 2
 
0.4%
1 63
12.6%
2 24
 
4.8%
3 17
 
3.4%
4 16
 
3.2%
5 5
 
1.0%
6 3
 
0.6%
7 1
 
0.2%
8 1
 
0.2%
9 2
 
0.4%
ValueCountFrequency (%)
100 1
0.2%
87 1
0.2%
42 1
0.2%
33 1
0.2%
28 1
0.2%
27 2
0.4%
20 1
0.2%
17 1
0.2%
16 2
0.4%
15 1
0.2%

상용종사자_여자(emp_sa_f)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)12.6%
Missing341
Missing (%)68.2%
Infinite0
Infinite (%)0.0%
Mean4.0880503
Minimum0
Maximum70
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:41.926349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile12.6
Maximum70
Range70
Interquartile range (IQR)2

Descriptive statistics

Standard deviation8.0625589
Coefficient of variation (CV)1.972226
Kurtosis34.557994
Mean4.0880503
Median Absolute Deviation (MAD)1
Skewness5.3484731
Sum650
Variance65.004856
MonotonicityNot monotonic
2023-12-10T23:49:42.313272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 65
 
13.0%
2 35
 
7.0%
3 20
 
4.0%
4 9
 
1.8%
8 5
 
1.0%
6 4
 
0.8%
5 4
 
0.8%
7 2
 
0.4%
9 2
 
0.4%
12 2
 
0.4%
Other values (10) 11
 
2.2%
(Missing) 341
68.2%
ValueCountFrequency (%)
0 2
 
0.4%
1 65
13.0%
2 35
7.0%
3 20
 
4.0%
4 9
 
1.8%
5 4
 
0.8%
6 4
 
0.8%
7 2
 
0.4%
8 5
 
1.0%
9 2
 
0.4%
ValueCountFrequency (%)
70 1
0.2%
47 1
0.2%
34 1
0.2%
33 1
0.2%
25 1
0.2%
22 1
0.2%
20 1
0.2%
18 1
0.2%
12 2
0.4%
10 1
0.2%

상용종사자_합계(emp_sa)
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)14.5%
Missing286
Missing (%)57.2%
Infinite0
Infinite (%)0.0%
Mean9.6495327
Minimum1
Maximum525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:42.459423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile25.35
Maximum525
Range524
Interquartile range (IQR)4

Descriptive statistics

Standard deviation41.153025
Coefficient of variation (CV)4.2647686
Kurtosis122.45169
Mean9.6495327
Median Absolute Deviation (MAD)1
Skewness10.468012
Sum2065
Variance1693.5714
MonotonicityNot monotonic
2023-12-10T23:49:42.585782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 66
 
13.2%
2 44
 
8.8%
3 23
 
4.6%
4 18
 
3.6%
5 10
 
2.0%
7 9
 
1.8%
6 6
 
1.2%
13 5
 
1.0%
8 4
 
0.8%
9 3
 
0.6%
Other values (21) 26
 
5.2%
(Missing) 286
57.2%
ValueCountFrequency (%)
1 66
13.2%
2 44
8.8%
3 23
 
4.6%
4 18
 
3.6%
5 10
 
2.0%
6 6
 
1.2%
7 9
 
1.8%
8 4
 
0.8%
9 3
 
0.6%
10 2
 
0.4%
ValueCountFrequency (%)
525 1
0.2%
259 1
0.2%
109 1
0.2%
80 1
0.2%
63 1
0.2%
50 1
0.2%
46 1
0.2%
34 1
0.2%
33 1
0.2%
32 1
0.2%

임시일용종사자_남자(emp_im_m)
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)19.4%
Missing464
Missing (%)92.8%
Infinite0
Infinite (%)0.0%
Mean2.4444444
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:42.699989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile6
Maximum21
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.5732694
Coefficient of variation (CV)1.461792
Kurtosis21.810763
Mean2.4444444
Median Absolute Deviation (MAD)0
Skewness4.4074069
Sum88
Variance12.768254
MonotonicityNot monotonic
2023-12-10T23:49:42.812392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 20
 
4.0%
2 9
 
1.8%
5 2
 
0.4%
3 2
 
0.4%
9 1
 
0.2%
4 1
 
0.2%
21 1
 
0.2%
(Missing) 464
92.8%
ValueCountFrequency (%)
1 20
4.0%
2 9
1.8%
3 2
 
0.4%
4 1
 
0.2%
5 2
 
0.4%
9 1
 
0.2%
21 1
 
0.2%
ValueCountFrequency (%)
21 1
 
0.2%
9 1
 
0.2%
5 2
 
0.4%
4 1
 
0.2%
3 2
 
0.4%
2 9
1.8%
1 20
4.0%

임시일용종사자_여자(emp_im_f)
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)13.6%
Missing434
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean2.5151515
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:42.926527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile8.75
Maximum22
Range21
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.1961243
Coefficient of variation (CV)1.6683386
Kurtosis13.997815
Mean2.5151515
Median Absolute Deviation (MAD)0
Skewness3.7652361
Sum166
Variance17.607459
MonotonicityNot monotonic
2023-12-10T23:49:43.024265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 46
 
9.2%
2 7
 
1.4%
3 4
 
0.8%
5 3
 
0.6%
4 2
 
0.4%
22 1
 
0.2%
19 1
 
0.2%
20 1
 
0.2%
10 1
 
0.2%
(Missing) 434
86.8%
ValueCountFrequency (%)
1 46
9.2%
2 7
 
1.4%
3 4
 
0.8%
4 2
 
0.4%
5 3
 
0.6%
10 1
 
0.2%
19 1
 
0.2%
20 1
 
0.2%
22 1
 
0.2%
ValueCountFrequency (%)
22 1
 
0.2%
20 1
 
0.2%
19 1
 
0.2%
10 1
 
0.2%
5 3
 
0.6%
4 2
 
0.4%
3 4
 
0.8%
2 7
 
1.4%
1 46
9.2%

임시일용종사자_합계(emp_im)
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)17.8%
Missing427
Missing (%)85.4%
Infinite0
Infinite (%)0.0%
Mean3.6575342
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:43.143593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile12.8
Maximum68
Range67
Interquartile range (IQR)2

Descriptive statistics

Standard deviation8.3868601
Coefficient of variation (CV)2.2930366
Kurtosis49.447448
Mean3.6575342
Median Absolute Deviation (MAD)0
Skewness6.6020873
Sum267
Variance70.339422
MonotonicityNot monotonic
2023-12-10T23:49:43.263447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 38
 
7.6%
2 13
 
2.6%
3 9
 
1.8%
5 3
 
0.6%
4 2
 
0.4%
15 1
 
0.2%
12 1
 
0.2%
14 1
 
0.2%
8 1
 
0.2%
10 1
 
0.2%
Other values (3) 3
 
0.6%
(Missing) 427
85.4%
ValueCountFrequency (%)
1 38
7.6%
2 13
 
2.6%
3 9
 
1.8%
4 2
 
0.4%
5 3
 
0.6%
7 1
 
0.2%
8 1
 
0.2%
10 1
 
0.2%
12 1
 
0.2%
14 1
 
0.2%
ValueCountFrequency (%)
68 1
 
0.2%
19 1
 
0.2%
15 1
 
0.2%
14 1
 
0.2%
12 1
 
0.2%
10 1
 
0.2%
8 1
 
0.2%
7 1
 
0.2%
5 3
0.6%
4 2
0.4%

무급(기타)종사자_남자(emp_mo_m)
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)66.7%
Missing491
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean2.3333333
Minimum0
Maximum10
Zeros3
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:43.391874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile7.6
Maximum10
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.2015621
Coefficient of variation (CV)1.3720981
Kurtosis4.4997026
Mean2.3333333
Median Absolute Deviation (MAD)1
Skewness2.0210082
Sum21
Variance10.25
MonotonicityNot monotonic
2023-12-10T23:49:43.512213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 3
 
0.6%
1 2
 
0.4%
2 1
 
0.2%
3 1
 
0.2%
10 1
 
0.2%
4 1
 
0.2%
(Missing) 491
98.2%
ValueCountFrequency (%)
0 3
0.6%
1 2
0.4%
2 1
 
0.2%
3 1
 
0.2%
4 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%
2 1
 
0.2%
1 2
0.4%
0 3
0.6%

무급(기타)종사자_여자(emp_mo_m)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
494 
2
 
2
0
 
2
19
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.966
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 494
98.8%
2 2
 
0.4%
0 2
 
0.4%
19 1
 
0.2%
6 1
 
0.2%

Length

2023-12-10T23:49:43.636611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:49:43.738235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 494
98.8%
2 2
 
0.4%
0 2
 
0.4%
19 1
 
0.2%
6 1
 
0.2%

무급(기타)종사자_합계(emp_mo)
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)64.7%
Missing483
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean7.1176471
Minimum0
Maximum37
Zeros3
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:43.836702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38
95-th percentile28.2
Maximum37
Range37
Interquartile range (IQR)7

Descriptive statistics

Standard deviation10.427622
Coefficient of variation (CV)1.4650378
Kurtosis3.6843791
Mean7.1176471
Median Absolute Deviation (MAD)3
Skewness2.0259466
Sum121
Variance108.73529
MonotonicityNot monotonic
2023-12-10T23:49:43.999871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 4
 
0.8%
0 3
 
0.6%
3 2
 
0.4%
2 1
 
0.2%
26 1
 
0.2%
6 1
 
0.2%
18 1
 
0.2%
8 1
 
0.2%
37 1
 
0.2%
5 1
 
0.2%
(Missing) 483
96.6%
ValueCountFrequency (%)
0 3
0.6%
1 4
0.8%
2 1
 
0.2%
3 2
0.4%
5 1
 
0.2%
6 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
18 1
 
0.2%
26 1
 
0.2%
ValueCountFrequency (%)
37 1
 
0.2%
26 1
 
0.2%
18 1
 
0.2%
9 1
 
0.2%
8 1
 
0.2%
6 1
 
0.2%
5 1
 
0.2%
3 2
0.4%
2 1
 
0.2%
1 4
0.8%

종사자_남자계(emp_to_m)
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)5.5%
Missing116
Missing (%)23.2%
Infinite0
Infinite (%)0.0%
Mean3.9817708
Minimum1
Maximum303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:44.202134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile8
Maximum303
Range302
Interquartile range (IQR)1

Descriptive statistics

Standard deviation18.508968
Coefficient of variation (CV)4.6484263
Kurtosis187.64765
Mean3.9817708
Median Absolute Deviation (MAD)0
Skewness12.671042
Sum1529
Variance342.58191
MonotonicityNot monotonic
2023-12-10T23:49:44.344412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 262
52.4%
2 47
 
9.4%
3 25
 
5.0%
4 11
 
2.2%
6 11
 
2.2%
5 5
 
1.0%
8 4
 
0.8%
10 3
 
0.6%
37 2
 
0.4%
7 2
 
0.4%
Other values (11) 12
 
2.4%
(Missing) 116
23.2%
ValueCountFrequency (%)
1 262
52.4%
2 47
 
9.4%
3 25
 
5.0%
4 11
 
2.2%
5 5
 
1.0%
6 11
 
2.2%
7 2
 
0.4%
8 4
 
0.8%
10 3
 
0.6%
11 2
 
0.4%
ValueCountFrequency (%)
303 1
0.2%
139 1
0.2%
93 1
0.2%
84 1
0.2%
45 1
0.2%
37 2
0.4%
32 1
0.2%
30 1
0.2%
29 1
0.2%
21 1
0.2%

종사자_여자계(emp_to_f)
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)6.5%
Missing175
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean3.7692308
Minimum1
Maximum130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:44.528598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile8.8
Maximum130
Range129
Interquartile range (IQR)2

Descriptive statistics

Standard deviation10.948208
Coefficient of variation (CV)2.9046265
Kurtosis75.144984
Mean3.7692308
Median Absolute Deviation (MAD)1
Skewness8.0748796
Sum1225
Variance119.86325
MonotonicityNot monotonic
2023-12-10T23:49:44.702011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 156
31.2%
2 77
15.4%
3 39
 
7.8%
4 14
 
2.8%
5 8
 
1.6%
6 6
 
1.2%
8 5
 
1.0%
7 3
 
0.6%
9 3
 
0.6%
10 3
 
0.6%
Other values (11) 11
 
2.2%
(Missing) 175
35.0%
ValueCountFrequency (%)
1 156
31.2%
2 77
15.4%
3 39
 
7.8%
4 14
 
2.8%
5 8
 
1.6%
6 6
 
1.2%
7 3
 
0.6%
8 5
 
1.0%
9 3
 
0.6%
10 3
 
0.6%
ValueCountFrequency (%)
130 1
0.2%
94 1
0.2%
67 1
0.2%
64 1
0.2%
50 1
0.2%
43 1
0.2%
31 1
0.2%
28 1
0.2%
16 1
0.2%
14 1
0.2%

종사자_총합계(emp_to)
Real number (ℝ)

Distinct34
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.79
Minimum1
Maximum172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:49:44.844129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile14
Maximum172
Range171
Interquartile range (IQR)2

Descriptive statistics

Standard deviation14.021809
Coefficient of variation (CV)2.9273087
Kurtosis82.928067
Mean4.79
Median Absolute Deviation (MAD)1
Skewness8.4265305
Sum2395
Variance196.61112
MonotonicityNot monotonic
2023-12-10T23:49:44.979576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 208
41.6%
2 121
24.2%
3 51
 
10.2%
4 28
 
5.6%
5 23
 
4.6%
6 13
 
2.6%
7 6
 
1.2%
10 6
 
1.2%
8 5
 
1.0%
11 4
 
0.8%
Other values (24) 35
 
7.0%
ValueCountFrequency (%)
1 208
41.6%
2 121
24.2%
3 51
 
10.2%
4 28
 
5.6%
5 23
 
4.6%
6 13
 
2.6%
7 6
 
1.2%
8 5
 
1.0%
9 3
 
0.6%
10 6
 
1.2%
ValueCountFrequency (%)
172 1
0.2%
160 1
0.2%
107 1
0.2%
100 1
0.2%
94 1
0.2%
60 1
0.2%
54 1
0.2%
43 1
0.2%
37 1
0.2%
34 1
0.2%

Sample

한국행정구역분류(zone_c)성별(d_sex)대표자연령(출생연도)(d_age)법인구분(josic_c)사업체구분(kubun_c)연도(chang_y)월(chang_m)한국표준산업분류(snl_b)자영업자_남자수(emp_ja_m)자영업자_여자수(emp_ja_f)자영업자_합계(emp_ja)무급가족종사자_남자수(emp_mu_m)무급가족종사자_여자수(emp_mu_f)무급가족종사자_합계(emp_mu)상용종사자_남자(emp_sa_m)상용종사자_여자(emp_sa_f)상용종사자_합계(emp_sa)임시일용종사자_남자(emp_im_m)임시일용종사자_여자(emp_im_f)임시일용종사자_합계(emp_im)무급(기타)종사자_남자(emp_mo_m)무급(기타)종사자_여자(emp_mo_m)무급(기타)종사자_합계(emp_mo)종사자_남자계(emp_to_m)종사자_여자계(emp_to_f)종사자_총합계(emp_to)
01122060119574201221752111<NA>1<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>1
1111205211982220085142312<NA>11<NA><NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA>2<NA>2
21119074119682200631862021<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>1
311130622196812008101862021<NA>1<NA><NA>1<NA><NA>63<NA><NA><NA><NA><NA><NA>122
41102054219591201351872101<NA>1<NA><NA><NA>1<NA><NA><NA><NA>1<NA><NA><NA>2<NA>5
51101053119651200781961221<NA>1<NA><NA>1<NA><NA><NA><NA><NA>5<NA><NA><NA>1104
611200681<NA>22008121464131<NA><NA>1<NA><NA><NA><NA>4<NA><NA><NA><NA><NA><NA>112
71105058119801199912125913<NA>11<NA>1<NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA>83
811040681<NA>41997101562201<NA>1<NA><NA>1<NA><NA>1<NA><NA><NA><NA><NA>2<NA><NA>1
91125053219721200171424121<NA>1<NA><NA><NA><NA>12212<NA><NA><NA>147
한국행정구역분류(zone_c)성별(d_sex)대표자연령(출생연도)(d_age)법인구분(josic_c)사업체구분(kubun_c)연도(chang_y)월(chang_m)한국표준산업분류(snl_b)자영업자_남자수(emp_ja_m)자영업자_여자수(emp_ja_f)자영업자_합계(emp_ja)무급가족종사자_남자수(emp_mu_m)무급가족종사자_여자수(emp_mu_f)무급가족종사자_합계(emp_mu)상용종사자_남자(emp_sa_m)상용종사자_여자(emp_sa_f)상용종사자_합계(emp_sa)임시일용종사자_남자(emp_im_m)임시일용종사자_여자(emp_im_f)임시일용종사자_합계(emp_im)무급(기타)종사자_남자(emp_mo_m)무급(기타)종사자_여자(emp_mo_m)무급(기타)종사자_합계(emp_mo)종사자_남자계(emp_to_m)종사자_여자계(emp_to_f)종사자_총합계(emp_to)
490112205211948119975195310111<NA><NA><NA>871<NA><NA>4<NA><NA><NA><NA>1943
49111010731<NA>1200641478231<NA>1<NA><NA><NA><NA>11<NA>1<NA><NA><NA><NA><NA><NA>1
49211240691196012011101465941<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>172
4931124080219441200051424121<NA>1<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA>1110
4941117070119681200871478131<NA>1<NA><NA><NA><NA><NA>18<NA><NA><NA><NA><NA><NA>3213
495111205211964120101346413<NA><NA>1<NA><NA><NA>2<NA>2<NA><NA><NA><NA><NA><NA>612
4961101061119721200412191229<NA><NA>1<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA><NA>111
497111506511946120126149231<NA><NA>11<NA><NA><NA>32<NA><NA><NA><NA><NA><NA>122
498112306021981120017185612<NA>11<NA><NA><NA><NA><NA>20<NA>1<NA><NA><NA><NA>125
4991119054119642199891662021<NA>1<NA>1<NA><NA>6<NA><NA><NA><NA><NA><NA><NA>1<NA>1