Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory66.5 B

Variable types

Text1
Numeric5
DateTime1

Dataset

Description경상북도 안동시 소재 사업체 수 및 종사자 수의 데이터(읍면동명, 총 사업체수, 여성대표자 사업체수, 총 총사자수, 남자 종사자수, 여자 종사자수 데이터기준일)를 연도말 기준으로 제공합니다.
URLhttps://www.data.go.kr/data/15116971/fileData.do

Alerts

데이터기준일 has constant value ""Constant
총 사업체수(개) is highly overall correlated with 여성대표자 사업체수(개) and 3 other fieldsHigh correlation
여성대표자 사업체수(개) is highly overall correlated with 총 사업체수(개) and 3 other fieldsHigh correlation
총 종사자수(명) is highly overall correlated with 총 사업체수(개) and 3 other fieldsHigh correlation
남자 종사자수(명) is highly overall correlated with 총 사업체수(개) and 3 other fieldsHigh correlation
여자 종사자수(명) is highly overall correlated with 총 사업체수(개) and 3 other fieldsHigh correlation
읍면동명 has unique valuesUnique
총 사업체수(개) has unique valuesUnique
여성대표자 사업체수(개) has unique valuesUnique
총 종사자수(명) has unique valuesUnique
남자 종사자수(명) has unique valuesUnique
여자 종사자수(명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:04:31.216114
Analysis finished2023-12-12 21:04:33.766675
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T06:04:33.896118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9583333
Min length2

Characters and Unicode

Total characters71
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row풍산읍
2nd row와룡면
3rd row북후면
4th row서후면
5th row풍천면
ValueCountFrequency (%)
풍산읍 1
 
4.2%
와룡면 1
 
4.2%
송하동 1
 
4.2%
옥동 1
 
4.2%
안기동 1
 
4.2%
평화동 1
 
4.2%
태화동 1
 
4.2%
서구동 1
 
4.2%
용상동 1
 
4.2%
명륜동 1
 
4.2%
Other values (14) 14
58.3%
2023-12-13T06:04:34.171874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 13
18.3%
동 11
 
15.5%
남 3
 
4.2%
안 3
 
4.2%
후 3
 
4.2%
화 2
 
2.8%
구 2
 
2.8%
산 2
 
2.8%
하 2
 
2.8%
임 2
 
2.8%
Other values (26) 28
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 13
18.3%
동 11
 
15.5%
남 3
 
4.2%
안 3
 
4.2%
후 3
 
4.2%
화 2
 
2.8%
구 2
 
2.8%
산 2
 
2.8%
하 2
 
2.8%
임 2
 
2.8%
Other values (26) 28
39.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 13
18.3%
동 11
 
15.5%
남 3
 
4.2%
안 3
 
4.2%
후 3
 
4.2%
화 2
 
2.8%
구 2
 
2.8%
산 2
 
2.8%
하 2
 
2.8%
임 2
 
2.8%
Other values (26) 28
39.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 13
18.3%
동 11
 
15.5%
남 3
 
4.2%
안 3
 
4.2%
후 3
 
4.2%
화 2
 
2.8%
구 2
 
2.8%
산 2
 
2.8%
하 2
 
2.8%
임 2
 
2.8%
Other values (26) 28
39.4%

총 사업체수(개)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean837.20833
Minimum123
Maximum2576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T06:04:34.296913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum123
5-th percentile129
Q1239.5
median491.5
Q31632.25
95-th percentile2026
Maximum2576
Range2453
Interquartile range (IQR)1392.75

Descriptive statistics

Standard deviation779.42626
Coefficient of variation (CV)0.93098245
Kurtosis-0.70415519
Mean837.20833
Median Absolute Deviation (MAD)329
Skewness0.89131058
Sum20093
Variance607505.3
MonotonicityNot monotonic
2023-12-13T06:04:34.464541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1617 1
 
4.2%
123 1
 
4.2%
1733 1
 
4.2%
1147 1
 
4.2%
2009 1
 
4.2%
499 1
 
4.2%
485 1
 
4.2%
1946 1
 
4.2%
1678 1
 
4.2%
2029 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
123 1
4.2%
126 1
4.2%
146 1
4.2%
179 1
4.2%
206 1
4.2%
229 1
4.2%
243 1
4.2%
248 1
4.2%
273 1
4.2%
316 1
4.2%
ValueCountFrequency (%)
2576 1
4.2%
2029 1
4.2%
2009 1
4.2%
1946 1
4.2%
1733 1
4.2%
1678 1
4.2%
1617 1
4.2%
1147 1
4.2%
938 1
4.2%
532 1
4.2%

여성대표자 사업체수(개)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean303.16667
Minimum41
Maximum1035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T06:04:34.585868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile42.15
Q172.25
median149.5
Q3428
95-th percentile918.5
Maximum1035
Range994
Interquartile range (IQR)355.75

Descriptive statistics

Standard deviation313.05516
Coefficient of variation (CV)1.0326174
Kurtosis0.12689921
Mean303.16667
Median Absolute Deviation (MAD)103
Skewness1.1735272
Sum7276
Variance98003.536
MonotonicityNot monotonic
2023-12-13T06:04:34.718698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
403 1
 
4.2%
41 1
 
4.2%
503 1
 
4.2%
400 1
 
4.2%
941 1
 
4.2%
165 1
 
4.2%
207 1
 
4.2%
648 1
 
4.2%
762 1
 
4.2%
791 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
41 1
4.2%
42 1
4.2%
43 1
4.2%
50 1
4.2%
55 1
4.2%
61 1
4.2%
76 1
4.2%
89 1
4.2%
97 1
4.2%
102 1
4.2%
ValueCountFrequency (%)
1035 1
4.2%
941 1
4.2%
791 1
4.2%
762 1
4.2%
648 1
4.2%
503 1
4.2%
403 1
4.2%
400 1
4.2%
352 1
4.2%
207 1
4.2%

총 종사자수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2873
Minimum209
Maximum7225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T06:04:34.838185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum209
5-th percentile232.2
Q1793
median1543.5
Q35632
95-th percentile6833.85
Maximum7225
Range7016
Interquartile range (IQR)4839

Descriptive statistics

Standard deviation2585.6875
Coefficient of variation (CV)0.89999565
Kurtosis-1.352644
Mean2873
Median Absolute Deviation (MAD)1287.5
Skewness0.6306686
Sum68952
Variance6685779.9
MonotonicityNot monotonic
2023-12-13T06:04:34.941143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
6124 1
 
4.2%
209 1
 
4.2%
6683 1
 
4.2%
3319 1
 
4.2%
7225 1
 
4.2%
1326 1
 
4.2%
1374 1
 
4.2%
4155 1
 
4.2%
6344 1
 
4.2%
6799 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
209 1
4.2%
222 1
4.2%
290 1
4.2%
555 1
4.2%
614 1
4.2%
742 1
4.2%
810 1
4.2%
825 1
4.2%
1100 1
4.2%
1136 1
4.2%
ValueCountFrequency (%)
7225 1
4.2%
6840 1
4.2%
6799 1
4.2%
6683 1
4.2%
6344 1
4.2%
6124 1
4.2%
5468 1
4.2%
4155 1
4.2%
3358 1
4.2%
3319 1
4.2%

남자 종사자수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1618.0833
Minimum113
Maximum4182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T06:04:35.048014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum113
5-th percentile148.25
Q1443.25
median857
Q33077.75
95-th percentile3979.2
Maximum4182
Range4069
Interquartile range (IQR)2634.5

Descriptive statistics

Standard deviation1428.7508
Coefficient of variation (CV)0.88298965
Kurtosis-1.3125289
Mean1618.0833
Median Absolute Deviation (MAD)696.5
Skewness0.58761625
Sum38834
Variance2041328.9
MonotonicityNot monotonic
2023-12-13T06:04:35.165488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4182 1
 
4.2%
113 1
 
4.2%
4059 1
 
4.2%
1922 1
 
4.2%
3395 1
 
4.2%
692 1
 
4.2%
640 1
 
4.2%
2436 1
 
4.2%
2976 1
 
4.2%
3527 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
113 1
4.2%
143 1
4.2%
178 1
4.2%
293 1
4.2%
371 1
4.2%
426 1
4.2%
449 1
4.2%
518 1
4.2%
545 1
4.2%
567 1
4.2%
ValueCountFrequency (%)
4182 1
4.2%
4059 1
4.2%
3527 1
4.2%
3469 1
4.2%
3395 1
4.2%
3383 1
4.2%
2976 1
4.2%
2436 1
4.2%
2063 1
4.2%
1922 1
4.2%

여자 종사자수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1254.9167
Minimum79
Maximum3830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T06:04:35.313426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum79
5-th percentile98.4
Q1275.5
median666.5
Q31956.25
95-th percentile3443.65
Maximum3830
Range3751
Interquartile range (IQR)1680.75

Descriptive statistics

Standard deviation1228.8938
Coefficient of variation (CV)0.97926331
Kurtosis-0.47332166
Mean1254.9167
Median Absolute Deviation (MAD)562.5
Skewness0.95649418
Sum30118
Variance1510180.1
MonotonicityNot monotonic
2023-12-13T06:04:35.433220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1942 1
 
4.2%
96 1
 
4.2%
2624 1
 
4.2%
1397 1
 
4.2%
3830 1
 
4.2%
634 1
 
4.2%
734 1
 
4.2%
1719 1
 
4.2%
3368 1
 
4.2%
3272 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
79 1
4.2%
96 1
4.2%
112 1
4.2%
243 1
4.2%
248 1
4.2%
262 1
4.2%
280 1
4.2%
293 1
4.2%
384 1
4.2%
533 1
4.2%
ValueCountFrequency (%)
3830 1
4.2%
3457 1
4.2%
3368 1
4.2%
3272 1
4.2%
2624 1
4.2%
1999 1
4.2%
1942 1
4.2%
1719 1
4.2%
1397 1
4.2%
1295 1
4.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2021-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-13T06:04:35.537173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:35.629712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:04:33.077920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.418785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.850341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.239053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.634775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:33.192967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.490909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.917489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.314693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.704044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:33.300125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.600271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.986897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.395039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.779073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:33.386259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.688484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.069098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.471536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.864972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:33.478803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:31.777017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.156985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.555359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:04:32.955202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:04:35.701663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명총 사업체수(개)여성대표자 사업체수(개)총 종사자수(명)남자 종사자수(명)여자 종사자수(명)
읍면동명1.0001.0001.0001.0001.0001.000
총 사업체수(개)1.0001.0000.9290.8300.7670.848
여성대표자 사업체수(개)1.0000.9291.0000.7860.8070.921
총 종사자수(명)1.0000.8300.7861.0000.9140.972
남자 종사자수(명)1.0000.7670.8070.9141.0000.840
여자 종사자수(명)1.0000.8480.9210.9720.8401.000
2023-12-13T06:04:35.801021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총 사업체수(개)여성대표자 사업체수(개)총 종사자수(명)남자 종사자수(명)여자 종사자수(명)
총 사업체수(개)1.0000.9710.9380.8960.921
여성대표자 사업체수(개)0.9711.0000.9210.8560.930
총 종사자수(명)0.9380.9211.0000.9630.957
남자 종사자수(명)0.8960.8560.9631.0000.904
여자 종사자수(명)0.9210.9300.9570.9041.000

Missing values

2023-12-13T06:04:33.599378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:04:33.720468image/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

읍면동명총 사업체수(개)여성대표자 사업체수(개)총 종사자수(명)남자 종사자수(명)여자 종사자수(명)데이터기준일
0풍산읍16174036124418219422021-12-31
1와룡면3171028255452802021-12-31
2북후면27310311365186182021-12-31
3서후면532134172110226992021-12-31
4풍천면9383525468346919992021-12-31
5일직면316976143712432021-12-31
6남후면2295011005675332021-12-31
7남선면24861171314652482021-12-31
8임하면206427424492932021-12-31
9길안면243895552932622021-12-31
읍면동명총 사업체수(개)여성대표자 사업체수(개)총 종사자수(명)남자 종사자수(명)여자 종사자수(명)데이터기준일
14중구동257610356840338334572021-12-31
15명륜동4981763358206312952021-12-31
16용상동20297916799352732722021-12-31
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