Overview

Dataset statistics

Number of variables27
Number of observations123
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.6 KiB
Average record size in memory230.1 B

Variable types

Text2
Numeric13
Categorical12

Dataset

Description부산광역시연제구_광제조업현황_20211231
Author부산광역시 연제구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15025069

Alerts

거제1동 종사자수 is highly imbalanced (53.1%)Imbalance
거제2동 종사자수 is highly imbalanced (59.1%)Imbalance
거제3동 종사자수 is highly imbalanced (52.2%)Imbalance
거제4동 종사자수 is highly imbalanced (60.7%)Imbalance
연산1동 종사자수 is highly imbalanced (55.2%)Imbalance
연산2동 종사자수 is highly imbalanced (52.2%)Imbalance
연산3동 종사자수 is highly imbalanced (68.2%)Imbalance
연산4동 종사자수 is highly imbalanced (55.2%)Imbalance
연산5동 종사자수 is highly imbalanced (51.1%)Imbalance
연산6동 종사자수 is highly imbalanced (52.0%)Imbalance
연산8동 종사자수 is highly imbalanced (54.5%)Imbalance
산업분류 has unique valuesUnique
연제구 사업체수 has 39 (31.7%) zerosZeros
거제1동 사업체수 has 81 (65.9%) zerosZeros
거제2동 사업체수 has 81 (65.9%) zerosZeros
거제3동 사업체수 has 75 (61.0%) zerosZeros
거제4동 사업체수 has 88 (71.5%) zerosZeros
연산1동 사업체수 has 78 (63.4%) zerosZeros
연산2동 사업체수 has 79 (64.2%) zerosZeros
연산3동 사업체수 has 103 (83.7%) zerosZeros
연산4동 사업체수 has 83 (67.5%) zerosZeros
연산5동 사업체수 has 75 (61.0%) zerosZeros
연산6동 사업체수 has 83 (67.5%) zerosZeros
연산8동 사업체수 has 86 (69.9%) zerosZeros
연산9동 사업체수 has 73 (59.3%) zerosZeros

Reproduction

Analysis started2023-12-10 16:52:18.284009
Analysis finished2023-12-10 16:52:18.842641
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산업분류
Text

UNIQUE 

Distinct123
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:52:19.162625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length25
Mean length17.178862
Min length8

Characters and Unicode

Total characters2113
Distinct characters192
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)100.0%

Sample

1st rowA.광업 (05 ~ 08)
2nd row05.석탄, 원유 및 천연가스 광업
3rd row051.석탄 광업
4th row052.원유 및 천연가스 채굴업
5th row06.금속 광업
ValueCountFrequency (%)
제조업 94
 
19.6%
및 67
 
14.0%
광업 7
 
1.5%
기타 6
 
1.3%
기계 5
 
1.0%
제품 5
 
1.0%
종이 5
 
1.0%
제외 4
 
0.8%
장비 4
 
0.8%
처리업 3
 
0.6%
Other values (251) 279
58.2%
2023-12-11T01:52:19.875761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
356
 
16.8%
제 149
 
7.1%
업 128
 
6.1%
. 123
 
5.8%
조 110
 
5.2%
1 83
 
3.9%
2 80
 
3.8%
및 67
 
3.2%
기 54
 
2.6%
3 52
 
2.5%
Other values (182) 911
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1246
59.0%
Space Separator 356
 
16.8%
Decimal Number 345
 
16.3%
Other Punctuation 158
 
7.5%
Open Punctuation 2
 
0.1%
Math Symbol 2
 
0.1%
Close Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 149
 
12.0%
업 128
 
10.3%
조 110
 
8.8%
및 67
 
5.4%
기 54
 
4.3%
품 51
 
4.1%
가 21
 
1.7%
비 21
 
1.7%
장 19
 
1.5%
물 19
 
1.5%
Other values (162) 607
48.7%
Decimal Number
ValueCountFrequency (%)
1 83
24.1%
2 80
23.2%
3 52
15.1%
0 38
11.0%
4 21
 
6.1%
6 16
 
4.6%
5 15
 
4.3%
8 14
 
4.1%
7 13
 
3.8%
9 13
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 123
77.8%
, 27
 
17.1%
; 6
 
3.8%
· 2
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
356
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1246
59.0%
Common 865
40.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 149
 
12.0%
업 128
 
10.3%
조 110
 
8.8%
및 67
 
5.4%
기 54
 
4.3%
품 51
 
4.1%
가 21
 
1.7%
비 21
 
1.7%
장 19
 
1.5%
물 19
 
1.5%
Other values (162) 607
48.7%
Common
ValueCountFrequency (%)
356
41.2%
. 123
 
14.2%
1 83
 
9.6%
2 80
 
9.2%
3 52
 
6.0%
0 38
 
4.4%
, 27
 
3.1%
4 21
 
2.4%
6 16
 
1.8%
5 15
 
1.7%
Other values (8) 54
 
6.2%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1246
59.0%
ASCII 865
40.9%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
356
41.2%
. 123
 
14.2%
1 83
 
9.6%
2 80
 
9.2%
3 52
 
6.0%
0 38
 
4.4%
, 27
 
3.1%
4 21
 
2.4%
6 16
 
1.8%
5 15
 
1.7%
Other values (9) 54
 
6.2%
Hangul
ValueCountFrequency (%)
제 149
 
12.0%
업 128
 
10.3%
조 110
 
8.8%
및 67
 
5.4%
기 54
 
4.3%
품 51
 
4.1%
가 21
 
1.7%
비 21
 
1.7%
장 19
 
1.5%
물 19
 
1.5%
Other values (162) 607
48.7%
None
ValueCountFrequency (%)
· 2
100.0%

연제구 사업체수
Real number (ℝ)

ZEROS 

Distinct38
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.195122
Minimum0
Maximum828
Zeros39
Zeros (%)31.7%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:20.068089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q311
95-th percentile74.3
Maximum828
Range828
Interquartile range (IQR)11

Descriptive statistics

Standard deviation78.418033
Coefficient of variation (CV)3.8830185
Kurtosis94.0809
Mean20.195122
Median Absolute Deviation (MAD)3
Skewness9.2210508
Sum2484
Variance6149.3878
MonotonicityNot monotonic
2023-12-11T01:52:20.246347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 39
31.7%
1 13
 
10.6%
4 10
 
8.1%
2 8
 
6.5%
6 8
 
6.5%
5 5
 
4.1%
3 3
 
2.4%
9 3
 
2.4%
51 2
 
1.6%
38 2
 
1.6%
Other values (28) 30
24.4%
ValueCountFrequency (%)
0 39
31.7%
1 13
 
10.6%
2 8
 
6.5%
3 3
 
2.4%
4 10
 
8.1%
5 5
 
4.1%
6 8
 
6.5%
7 1
 
0.8%
8 1
 
0.8%
9 3
 
2.4%
ValueCountFrequency (%)
828 1
0.8%
174 1
0.8%
136 1
0.8%
112 1
0.8%
99 1
0.8%
79 1
0.8%
75 1
0.8%
68 1
0.8%
53 1
0.8%
52 1
0.8%

연제구 종사자수
Text

Distinct51
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:52:20.439683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.5365854
Min length1

Characters and Unicode

Total characters189
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)30.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 39
31.7%
x 21
17.1%
6 4
 
3.3%
9 3
 
2.4%
5 2
 
1.6%
15 2
 
1.6%
61 2
 
1.6%
111 2
 
1.6%
11 2
 
1.6%
29 2
 
1.6%
Other values (41) 44
35.8%
2023-12-11T01:52:20.839487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
22.8%
1 27
14.3%
x 21
11.1%
6 20
10.6%
2 18
9.5%
9 14
 
7.4%
4 11
 
5.8%
5 10
 
5.3%
7 9
 
4.8%
8 8
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168
88.9%
Lowercase Letter 21
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
25.6%
1 27
16.1%
6 20
11.9%
2 18
10.7%
9 14
 
8.3%
4 11
 
6.5%
5 10
 
6.0%
7 9
 
5.4%
8 8
 
4.8%
3 8
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
x 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168
88.9%
Latin 21
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
25.6%
1 27
16.1%
6 20
11.9%
2 18
10.7%
9 14
 
8.3%
4 11
 
6.5%
5 10
 
6.0%
7 9
 
5.4%
8 8
 
4.8%
3 8
 
4.8%
Latin
ValueCountFrequency (%)
x 21
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 189
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
22.8%
1 27
14.3%
x 21
11.1%
6 20
10.6%
2 18
9.5%
9 14
 
7.4%
4 11
 
5.8%
5 10
 
5.3%
7 9
 
4.8%
8 8
 
4.2%

거제1동 사업체수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6097561
Minimum0
Maximum66
Zeros81
Zeros (%)65.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:21.016289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum66
Range66
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.2654846
Coefficient of variation (CV)3.892195
Kurtosis93.122474
Mean1.6097561
Median Absolute Deviation (MAD)0
Skewness9.1404429
Sum198
Variance39.256297
MonotonicityNot monotonic
2023-12-11T01:52:21.220240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 81
65.9%
1 16
 
13.0%
2 7
 
5.7%
4 6
 
4.9%
3 3
 
2.4%
7 2
 
1.6%
5 2
 
1.6%
6 2
 
1.6%
66 1
 
0.8%
11 1
 
0.8%
Other values (2) 2
 
1.6%
ValueCountFrequency (%)
0 81
65.9%
1 16
 
13.0%
2 7
 
5.7%
3 3
 
2.4%
4 6
 
4.9%
5 2
 
1.6%
6 2
 
1.6%
7 2
 
1.6%
10 1
 
0.8%
11 1
 
0.8%
ValueCountFrequency (%)
66 1
 
0.8%
12 1
 
0.8%
11 1
 
0.8%
10 1
 
0.8%
7 2
 
1.6%
6 2
 
1.6%
5 2
 
1.6%
4 6
4.9%
3 3
2.4%
2 7
5.7%

거제1동 종사자수
Categorical

IMBALANCE 

Distinct14
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
81 
x
23 
7
 
4
6
 
3
16
 
2
Other values (9)
10 

Length

Max length3
Median length1
Mean length1.0894309
Min length1

Unique

Unique8 ?
Unique (%)6.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 81
65.9%
x 23
 
18.7%
7 4
 
3.3%
6 3
 
2.4%
16 2
 
1.6%
20 2
 
1.6%
177 1
 
0.8%
12 1
 
0.8%
28 1
 
0.8%
22 1
 
0.8%
Other values (4) 4
 
3.3%

Length

2023-12-11T01:52:21.430738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 81
65.9%
x 23
 
18.7%
7 4
 
3.3%
6 3
 
2.4%
16 2
 
1.6%
20 2
 
1.6%
177 1
 
0.8%
12 1
 
0.8%
28 1
 
0.8%
22 1
 
0.8%
Other values (4) 4
 
3.3%

거제2동 사업체수
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.95121951
Minimum0
Maximum39
Zeros81
Zeros (%)65.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:21.604367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum39
Range39
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.6571369
Coefficient of variation (CV)3.8446824
Kurtosis97.881654
Mean0.95121951
Median Absolute Deviation (MAD)0
Skewness9.4387616
Sum117
Variance13.37465
MonotonicityNot monotonic
2023-12-11T01:52:21.780077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 81
65.9%
1 23
 
18.7%
2 10
 
8.1%
4 4
 
3.3%
5 2
 
1.6%
39 1
 
0.8%
6 1
 
0.8%
3 1
 
0.8%
ValueCountFrequency (%)
0 81
65.9%
1 23
 
18.7%
2 10
 
8.1%
3 1
 
0.8%
4 4
 
3.3%
5 2
 
1.6%
6 1
 
0.8%
39 1
 
0.8%
ValueCountFrequency (%)
39 1
 
0.8%
6 1
 
0.8%
5 2
 
1.6%
4 4
 
3.3%
3 1
 
0.8%
2 10
 
8.1%
1 23
 
18.7%
0 81
65.9%

거제2동 종사자수
Categorical

IMBALANCE 

Distinct11
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
81 
x
33 
178
 
1
5
 
1
77
 
1
Other values (6)
 
6

Length

Max length3
Median length1
Mean length1.0569106
Min length1

Unique

Unique9 ?
Unique (%)7.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 81
65.9%
x 33
26.8%
178 1
 
0.8%
5 1
 
0.8%
77 1
 
0.8%
71 1
 
0.8%
46 1
 
0.8%
12 1
 
0.8%
11 1
 
0.8%
8 1
 
0.8%

Length

2023-12-11T01:52:21.943345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 81
65.9%
x 33
26.8%
178 1
 
0.8%
5 1
 
0.8%
77 1
 
0.8%
71 1
 
0.8%
46 1
 
0.8%
12 1
 
0.8%
11 1
 
0.8%
8 1
 
0.8%

거제3동 사업체수
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1463415
Minimum0
Maximum88
Zeros75
Zeros (%)61.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:22.093683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8.8
Maximum88
Range88
Interquartile range (IQR)1

Descriptive statistics

Standard deviation8.5753009
Coefficient of variation (CV)3.9953107
Kurtosis84.13773
Mean2.1463415
Median Absolute Deviation (MAD)0
Skewness8.6371079
Sum264
Variance73.535786
MonotonicityNot monotonic
2023-12-11T01:52:22.208721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 75
61.0%
1 21
 
17.1%
2 9
 
7.3%
3 3
 
2.4%
6 3
 
2.4%
4 3
 
2.4%
11 2
 
1.6%
9 2
 
1.6%
88 1
 
0.8%
26 1
 
0.8%
Other values (3) 3
 
2.4%
ValueCountFrequency (%)
0 75
61.0%
1 21
 
17.1%
2 9
 
7.3%
3 3
 
2.4%
4 3
 
2.4%
5 1
 
0.8%
6 3
 
2.4%
7 1
 
0.8%
9 2
 
1.6%
11 2
 
1.6%
ValueCountFrequency (%)
88 1
 
0.8%
26 1
 
0.8%
20 1
 
0.8%
11 2
1.6%
9 2
1.6%
7 1
 
0.8%
6 3
2.4%
5 1
 
0.8%
4 3
2.4%
3 3
2.4%

거제3동 종사자수
Categorical

IMBALANCE 

Distinct15
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
75 
x
30 
36
 
2
78
 
2
12
 
2
Other values (10)
12 

Length

Max length3
Median length1
Mean length1.1219512
Min length1

Unique

Unique8 ?
Unique (%)6.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 75
61.0%
x 30
 
24.4%
36 2
 
1.6%
78 2
 
1.6%
12 2
 
1.6%
37 2
 
1.6%
5 2
 
1.6%
405 1
 
0.8%
46 1
 
0.8%
4 1
 
0.8%
Other values (5) 5
 
4.1%

Length

2023-12-11T01:52:22.360022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 75
61.0%
x 30
 
24.4%
36 2
 
1.6%
78 2
 
1.6%
12 2
 
1.6%
37 2
 
1.6%
5 2
 
1.6%
405 1
 
0.8%
46 1
 
0.8%
4 1
 
0.8%
Other values (5) 5
 
4.1%

거제4동 사업체수
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1707317
Minimum0
Maximum48
Zeros88
Zeros (%)71.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:22.507365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum48
Range48
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.7764918
Coefficient of variation (CV)4.0799201
Kurtosis77.580536
Mean1.1707317
Median Absolute Deviation (MAD)0
Skewness8.2470035
Sum144
Variance22.814874
MonotonicityNot monotonic
2023-12-11T01:52:22.649737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 88
71.5%
1 16
 
13.0%
2 9
 
7.3%
4 2
 
1.6%
3 2
 
1.6%
48 1
 
0.8%
8 1
 
0.8%
6 1
 
0.8%
15 1
 
0.8%
14 1
 
0.8%
ValueCountFrequency (%)
0 88
71.5%
1 16
 
13.0%
2 9
 
7.3%
3 2
 
1.6%
4 2
 
1.6%
5 1
 
0.8%
6 1
 
0.8%
8 1
 
0.8%
14 1
 
0.8%
15 1
 
0.8%
ValueCountFrequency (%)
48 1
 
0.8%
15 1
 
0.8%
14 1
 
0.8%
8 1
 
0.8%
6 1
 
0.8%
5 1
 
0.8%
4 2
 
1.6%
3 2
 
1.6%
2 9
7.3%
1 16
13.0%

거제4동 종사자수
Categorical

IMBALANCE 

Distinct11
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
88 
x
25 
5
 
2
184
 
1
14
 
1
Other values (6)
 
6

Length

Max length3
Median length1
Mean length1.0569106
Min length1

Unique

Unique8 ?
Unique (%)6.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 88
71.5%
x 25
 
20.3%
5 2
 
1.6%
184 1
 
0.8%
14 1
 
0.8%
10 1
 
0.8%
9 1
 
0.8%
78 1
 
0.8%
73 1
 
0.8%
8 1
 
0.8%

Length

2023-12-11T01:52:22.788947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 88
71.5%
x 25
 
20.3%
5 2
 
1.6%
184 1
 
0.8%
14 1
 
0.8%
10 1
 
0.8%
9 1
 
0.8%
78 1
 
0.8%
73 1
 
0.8%
8 1
 
0.8%

연산1동 사업체수
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9512195
Minimum0
Maximum80
Zeros78
Zeros (%)63.4%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:22.915772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5.9
Maximum80
Range80
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.8738555
Coefficient of variation (CV)4.035351
Kurtosis80.705226
Mean1.9512195
Median Absolute Deviation (MAD)0
Skewness8.4101863
Sum240
Variance61.997601
MonotonicityNot monotonic
2023-12-11T01:52:23.028153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 78
63.4%
1 20
 
16.3%
2 8
 
6.5%
3 5
 
4.1%
4 4
 
3.3%
80 1
 
0.8%
21 1
 
0.8%
18 1
 
0.8%
10 1
 
0.8%
6 1
 
0.8%
Other values (3) 3
 
2.4%
ValueCountFrequency (%)
0 78
63.4%
1 20
 
16.3%
2 8
 
6.5%
3 5
 
4.1%
4 4
 
3.3%
5 1
 
0.8%
6 1
 
0.8%
10 1
 
0.8%
16 1
 
0.8%
17 1
 
0.8%
ValueCountFrequency (%)
80 1
 
0.8%
21 1
 
0.8%
18 1
 
0.8%
17 1
 
0.8%
16 1
 
0.8%
10 1
 
0.8%
6 1
 
0.8%
5 1
 
0.8%
4 4
3.3%
3 5
4.1%

연산1동 종사자수
Categorical

IMBALANCE 

Distinct17
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
78 
x
28 
12
 
2
7
 
2
198
 
1
Other values (12)
12 

Length

Max length3
Median length1
Mean length1.1138211
Min length1

Unique

Unique13 ?
Unique (%)10.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 78
63.4%
x 28
 
22.8%
12 2
 
1.6%
7 2
 
1.6%
198 1
 
0.8%
40 1
 
0.8%
35 1
 
0.8%
10 1
 
0.8%
4 1
 
0.8%
11 1
 
0.8%
Other values (7) 7
 
5.7%

Length

2023-12-11T01:52:23.155571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 78
63.4%
x 28
 
22.8%
12 2
 
1.6%
7 2
 
1.6%
5 1
 
0.8%
22 1
 
0.8%
45 1
 
0.8%
14 1
 
0.8%
15 1
 
0.8%
27 1
 
0.8%
Other values (7) 7
 
5.7%

연산2동 사업체수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6097561
Minimum0
Maximum66
Zeros79
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:23.268778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5.9
Maximum66
Range66
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.4307588
Coefficient of variation (CV)3.9948653
Kurtosis84.31872
Mean1.6097561
Median Absolute Deviation (MAD)0
Skewness8.6640031
Sum198
Variance41.354658
MonotonicityNot monotonic
2023-12-11T01:52:23.428431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 79
64.2%
1 21
 
17.1%
2 6
 
4.9%
4 5
 
4.1%
3 4
 
3.3%
6 2
 
1.6%
66 1
 
0.8%
21 1
 
0.8%
14 1
 
0.8%
5 1
 
0.8%
Other values (2) 2
 
1.6%
ValueCountFrequency (%)
0 79
64.2%
1 21
 
17.1%
2 6
 
4.9%
3 4
 
3.3%
4 5
 
4.1%
5 1
 
0.8%
6 2
 
1.6%
7 1
 
0.8%
8 1
 
0.8%
14 1
 
0.8%
ValueCountFrequency (%)
66 1
 
0.8%
21 1
 
0.8%
14 1
 
0.8%
8 1
 
0.8%
7 1
 
0.8%
6 2
 
1.6%
5 1
 
0.8%
4 5
4.1%
3 4
3.3%
2 6
4.9%

연산2동 종사자수
Categorical

IMBALANCE 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
79 
x
27 
11
 
4
4
 
3
27
 
2
Other values (7)
8 

Length

Max length3
Median length1
Mean length1.1138211
Min length1

Unique

Unique6 ?
Unique (%)4.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 79
64.2%
x 27
 
22.0%
11 4
 
3.3%
4 3
 
2.4%
27 2
 
1.6%
12 2
 
1.6%
165 1
 
0.8%
33 1
 
0.8%
21 1
 
0.8%
5 1
 
0.8%
Other values (2) 2
 
1.6%

Length

2023-12-11T01:52:23.611502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 79
64.2%
x 27
 
22.0%
11 4
 
3.3%
4 3
 
2.4%
27 2
 
1.6%
12 2
 
1.6%
165 1
 
0.8%
33 1
 
0.8%
21 1
 
0.8%
5 1
 
0.8%
Other values (2) 2
 
1.6%

연산3동 사업체수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.43902439
Minimum0
Maximum18
Zeros103
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:23.768880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.842781
Coefficient of variation (CV)4.1974455
Kurtosis69.696161
Mean0.43902439
Median Absolute Deviation (MAD)0
Skewness7.7518676
Sum54
Variance3.3958417
MonotonicityNot monotonic
2023-12-11T01:52:23.939475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 103
83.7%
1 11
 
8.9%
2 5
 
4.1%
18 1
 
0.8%
7 1
 
0.8%
5 1
 
0.8%
3 1
 
0.8%
ValueCountFrequency (%)
0 103
83.7%
1 11
 
8.9%
2 5
 
4.1%
3 1
 
0.8%
5 1
 
0.8%
7 1
 
0.8%
18 1
 
0.8%
ValueCountFrequency (%)
18 1
 
0.8%
7 1
 
0.8%
5 1
 
0.8%
3 1
 
0.8%
2 5
 
4.1%
1 11
 
8.9%
0 103
83.7%

연산3동 종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
103 
x
16 
26
 
1
12
 
1
9
 
1

Length

Max length2
Median length1
Mean length1.0162602
Min length1

Unique

Unique4 ?
Unique (%)3.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 103
83.7%
x 16
 
13.0%
26 1
 
0.8%
12 1
 
0.8%
9 1
 
0.8%
4 1
 
0.8%

Length

2023-12-11T01:52:24.093324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:52:24.234570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 103
83.7%
x 16
 
13.0%
26 1
 
0.8%
12 1
 
0.8%
9 1
 
0.8%
4 1
 
0.8%

연산4동 사업체수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9268293
Minimum0
Maximum79
Zeros83
Zeros (%)67.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:24.402198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile9
Maximum79
Range79
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.7693922
Coefficient of variation (CV)4.0322162
Kurtosis80.941159
Mean1.9268293
Median Absolute Deviation (MAD)0
Skewness8.4059038
Sum237
Variance60.363455
MonotonicityNot monotonic
2023-12-11T01:52:24.580920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 83
67.5%
1 19
 
15.4%
2 5
 
4.1%
9 4
 
3.3%
3 3
 
2.4%
10 2
 
1.6%
4 2
 
1.6%
79 1
 
0.8%
22 1
 
0.8%
19 1
 
0.8%
Other values (2) 2
 
1.6%
ValueCountFrequency (%)
0 83
67.5%
1 19
 
15.4%
2 5
 
4.1%
3 3
 
2.4%
4 2
 
1.6%
7 1
 
0.8%
8 1
 
0.8%
9 4
 
3.3%
10 2
 
1.6%
19 1
 
0.8%
ValueCountFrequency (%)
79 1
 
0.8%
22 1
 
0.8%
19 1
 
0.8%
10 2
 
1.6%
9 4
3.3%
8 1
 
0.8%
7 1
 
0.8%
4 2
 
1.6%
3 3
2.4%
2 5
4.1%

연산4동 종사자수
Categorical

IMBALANCE 

Distinct13
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
83 
x
24 
5
 
3
8
 
2
13
 
2
Other values (8)
9 

Length

Max length3
Median length1
Mean length1.0894309
Min length1

Unique

Unique7 ?
Unique (%)5.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 83
67.5%
x 24
 
19.5%
5 3
 
2.4%
8 2
 
1.6%
13 2
 
1.6%
15 2
 
1.6%
125 1
 
0.8%
34 1
 
0.8%
30 1
 
0.8%
18 1
 
0.8%
Other values (3) 3
 
2.4%

Length

2023-12-11T01:52:25.077467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 83
67.5%
x 24
 
19.5%
5 3
 
2.4%
8 2
 
1.6%
13 2
 
1.6%
15 2
 
1.6%
125 1
 
0.8%
34 1
 
0.8%
30 1
 
0.8%
18 1
 
0.8%
Other values (3) 3
 
2.4%

연산5동 사업체수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5853659
Minimum0
Maximum65
Zeros75
Zeros (%)61.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:25.229823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum65
Range65
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.1028438
Coefficient of variation (CV)3.8494861
Kurtosis97.382232
Mean1.5853659
Median Absolute Deviation (MAD)0
Skewness9.4074898
Sum195
Variance37.244702
MonotonicityNot monotonic
2023-12-11T01:52:25.348279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 75
61.0%
1 23
 
18.7%
2 6
 
4.9%
4 5
 
4.1%
3 4
 
3.3%
5 2
 
1.6%
6 2
 
1.6%
7 2
 
1.6%
65 1
 
0.8%
10 1
 
0.8%
Other values (2) 2
 
1.6%
ValueCountFrequency (%)
0 75
61.0%
1 23
 
18.7%
2 6
 
4.9%
3 4
 
3.3%
4 5
 
4.1%
5 2
 
1.6%
6 2
 
1.6%
7 2
 
1.6%
8 1
 
0.8%
9 1
 
0.8%
ValueCountFrequency (%)
65 1
 
0.8%
10 1
 
0.8%
9 1
 
0.8%
8 1
 
0.8%
7 2
 
1.6%
6 2
 
1.6%
5 2
 
1.6%
4 5
4.1%
3 4
3.3%
2 6
4.9%

연산5동 종사자수
Categorical

IMBALANCE 

Distinct14
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
75 
x
29 
5
 
4
32
 
3
14
 
2
Other values (9)
10 

Length

Max length3
Median length1
Mean length1.1219512
Min length1

Unique

Unique8 ?
Unique (%)6.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 75
61.0%
x 29
 
23.6%
5 4
 
3.3%
32 3
 
2.4%
14 2
 
1.6%
18 2
 
1.6%
418 1
 
0.8%
104 1
 
0.8%
4 1
 
0.8%
6 1
 
0.8%
Other values (4) 4
 
3.3%

Length

2023-12-11T01:52:25.483382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 75
61.0%
x 29
 
23.6%
5 4
 
3.3%
32 3
 
2.4%
14 2
 
1.6%
18 2
 
1.6%
418 1
 
0.8%
104 1
 
0.8%
4 1
 
0.8%
6 1
 
0.8%
Other values (4) 4
 
3.3%

연산6동 사업체수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9268293
Minimum0
Maximum79
Zeros83
Zeros (%)67.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:25.618565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum79
Range79
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.6202607
Coefficient of variation (CV)3.9548188
Kurtosis87.428103
Mean1.9268293
Median Absolute Deviation (MAD)0
Skewness8.8095828
Sum237
Variance58.068373
MonotonicityNot monotonic
2023-12-11T01:52:25.754520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 83
67.5%
1 11
 
8.9%
2 7
 
5.7%
4 6
 
4.9%
3 5
 
4.1%
5 3
 
2.4%
8 2
 
1.6%
7 2
 
1.6%
79 1
 
0.8%
19 1
 
0.8%
Other values (2) 2
 
1.6%
ValueCountFrequency (%)
0 83
67.5%
1 11
 
8.9%
2 7
 
5.7%
3 5
 
4.1%
4 6
 
4.9%
5 3
 
2.4%
7 2
 
1.6%
8 2
 
1.6%
13 1
 
0.8%
17 1
 
0.8%
ValueCountFrequency (%)
79 1
 
0.8%
19 1
 
0.8%
17 1
 
0.8%
13 1
 
0.8%
8 2
 
1.6%
7 2
 
1.6%
5 3
2.4%
4 6
4.9%
3 5
4.1%
2 7
5.7%

연산6동 종사자수
Categorical

IMBALANCE 

Distinct14
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
83 
x
18 
6
 
4
7
 
4
4
 
3
Other values (9)
11 

Length

Max length3
Median length1
Mean length1.0731707
Min length1

Unique

Unique7 ?
Unique (%)5.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 83
67.5%
x 18
 
14.6%
6 4
 
3.3%
7 4
 
3.3%
4 3
 
2.4%
31 2
 
1.6%
9 2
 
1.6%
140 1
 
0.8%
29 1
 
0.8%
10 1
 
0.8%
Other values (4) 4
 
3.3%

Length

2023-12-11T01:52:25.925139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 83
67.5%
x 18
 
14.6%
6 4
 
3.3%
7 4
 
3.3%
4 3
 
2.4%
31 2
 
1.6%
9 2
 
1.6%
140 1
 
0.8%
29 1
 
0.8%
10 1
 
0.8%
Other values (4) 4
 
3.3%

연산8동 사업체수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9756098
Minimum0
Maximum81
Zeros86
Zeros (%)69.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:26.086432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8.9
Maximum81
Range81
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.8421553
Coefficient of variation (CV)3.969486
Kurtosis85.978413
Mean1.9756098
Median Absolute Deviation (MAD)0
Skewness8.6869953
Sum243
Variance61.4994
MonotonicityNot monotonic
2023-12-11T01:52:26.246989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 86
69.9%
1 12
 
9.8%
3 8
 
6.5%
2 3
 
2.4%
4 3
 
2.4%
13 2
 
1.6%
8 2
 
1.6%
7 2
 
1.6%
16 2
 
1.6%
81 1
 
0.8%
Other values (2) 2
 
1.6%
ValueCountFrequency (%)
0 86
69.9%
1 12
 
9.8%
2 3
 
2.4%
3 8
 
6.5%
4 3
 
2.4%
7 2
 
1.6%
8 2
 
1.6%
9 1
 
0.8%
11 1
 
0.8%
13 2
 
1.6%
ValueCountFrequency (%)
81 1
 
0.8%
16 2
 
1.6%
13 2
 
1.6%
11 1
 
0.8%
9 1
 
0.8%
8 2
 
1.6%
7 2
 
1.6%
4 3
 
2.4%
3 8
6.5%
2 3
 
2.4%

연산8동 종사자수
Categorical

IMBALANCE 

Distinct16
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
86 
x
15 
8
 
4
4
 
3
81
 
2
Other values (11)
13 

Length

Max length3
Median length1
Mean length1.1056911
Min length1

Unique

Unique9 ?
Unique (%)7.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 86
69.9%
x 15
 
12.2%
8 4
 
3.3%
4 3
 
2.4%
81 2
 
1.6%
6 2
 
1.6%
30 2
 
1.6%
228 1
 
0.8%
17 1
 
0.8%
10 1
 
0.8%
Other values (6) 6
 
4.9%

Length

2023-12-11T01:52:26.401820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 86
69.9%
x 15
 
12.2%
8 4
 
3.3%
4 3
 
2.4%
81 2
 
1.6%
6 2
 
1.6%
30 2
 
1.6%
228 1
 
0.8%
17 1
 
0.8%
10 1
 
0.8%
Other values (6) 6
 
4.9%

연산9동 사업체수
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.902439
Minimum0
Maximum119
Zeros73
Zeros (%)59.3%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:26.534160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10.9
Maximum119
Range119
Interquartile range (IQR)2

Descriptive statistics

Standard deviation11.236223
Coefficient of variation (CV)3.8713036
Kurtosis95.188812
Mean2.902439
Median Absolute Deviation (MAD)0
Skewness9.2733712
Sum357
Variance126.2527
MonotonicityNot monotonic
2023-12-11T01:52:26.647664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 73
59.3%
1 14
 
11.4%
2 8
 
6.5%
3 7
 
5.7%
9 5
 
4.1%
5 3
 
2.4%
4 2
 
1.6%
7 2
 
1.6%
12 2
 
1.6%
22 1
 
0.8%
Other values (6) 6
 
4.9%
ValueCountFrequency (%)
0 73
59.3%
1 14
 
11.4%
2 8
 
6.5%
3 7
 
5.7%
4 2
 
1.6%
5 3
 
2.4%
6 1
 
0.8%
7 2
 
1.6%
9 5
 
4.1%
10 1
 
0.8%
ValueCountFrequency (%)
119 1
 
0.8%
22 1
 
0.8%
19 1
 
0.8%
13 1
 
0.8%
12 2
 
1.6%
11 1
 
0.8%
10 1
 
0.8%
9 5
4.1%
7 2
 
1.6%
6 1
 
0.8%

연산9동 종사자수
Categorical

Distinct22
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
73 
x
22 
76
 
2
15
 
2
7
 
2
Other values (17)
22 

Length

Max length3
Median length1
Mean length1.1707317
Min length1

Unique

Unique12 ?
Unique (%)9.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 73
59.3%
x 22
 
17.9%
76 2
 
1.6%
15 2
 
1.6%
7 2
 
1.6%
11 2
 
1.6%
6 2
 
1.6%
3 2
 
1.6%
33 2
 
1.6%
13 2
 
1.6%
Other values (12) 12
 
9.8%

Length

2023-12-11T01:52:26.873583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 73
59.3%
x 22
 
17.9%
76 2
 
1.6%
15 2
 
1.6%
7 2
 
1.6%
11 2
 
1.6%
6 2
 
1.6%
3 2
 
1.6%
33 2
 
1.6%
13 2
 
1.6%
Other values (12) 12
 
9.8%

Sample

산업분류연제구 사업체수연제구 종사자수거제1동 사업체수거제1동 종사자수거제2동 사업체수거제2동 종사자수거제3동 사업체수거제3동 종사자수거제4동 사업체수거제4동 종사자수연산1동 사업체수연산1동 종사자수연산2동 사업체수연산2동 종사자수연산3동 사업체수연산3동 종사자수연산4동 사업체수연산4동 종사자수연산5동 사업체수연산5동 종사자수연산6동 사업체수연산6동 종사자수연산8동 사업체수연산8동 종사자수연산9동 사업체수연산9동 종사자수
0A.광업 (05 ~ 08)00000000000000000000000000
105.석탄, 원유 및 천연가스 광업00000000000000000000000000
2051.석탄 광업00000000000000000000000000
3052.원유 및 천연가스 채굴업00000000000000000000000000
406.금속 광업00000000000000000000000000
5061.철 광업00000000000000000000000000
6062.비철금속 광업00000000000000000000000000
707.비금속광물 광업;연료용 제외00000000000000000000000000
8071.토사석 광업00000000000000000000000000
9072.기타 비금속광물 광업00000000000000000000000000
산업분류연제구 사업체수연제구 종사자수거제1동 사업체수거제1동 종사자수거제2동 사업체수거제2동 종사자수거제3동 사업체수거제3동 종사자수거제4동 사업체수거제4동 종사자수연산1동 사업체수연산1동 종사자수연산2동 사업체수연산2동 종사자수연산3동 사업체수연산3동 종사자수연산4동 사업체수연산4동 종사자수연산5동 사업체수연산5동 종사자수연산6동 사업체수연산6동 종사자수연산8동 사업체수연산8동 종사자수연산9동 사업체수연산9동 종사자수
11332.가구 제조업386100006121x2x41100351x2x781215
114320.가구 제조업386100006121x2x41100351x2x781215
11533.기타 제품 제조업11225612184893735174581834101393281316301333
116331.귀금속 및 장신용품 제조업661x1x00001x1x00001x00001x
117332.악기제조업00000000000000000000000000
118333.운동 및 경기용구 제조업4161x00000000001x1x0000001x
119334.인형,장난감 및 오락용품 제조업38000000000000001x001x001x
120339.그외 기타 제품 제조업992261016379373516447172x8118317716301018
12134.산업용 기계 및 장비 수리업4066462x452x1x34001x7184434913
122340.산업용 기계 및 장비 수리업4066462x452x1x34001x7184434913