Overview

Dataset statistics

Number of variables6
Number of observations110
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory51.2 B

Variable types

Numeric2
Categorical2
Text2

Dataset

Description농어촌정비법에 따른 도내 관광농원 지정 현황을 공개합니다. 시군 지역과 업체명, 유형, 매출액 비중, 고용임금 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3071902/fileData.do

Alerts

연번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:37:34.338251
Analysis finished2023-12-12 09:37:35.661975
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.5
Minimum1
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T18:37:35.757902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.45
Q128.25
median55.5
Q382.75
95-th percentile104.55
Maximum110
Range109
Interquartile range (IQR)54.5

Descriptive statistics

Standard deviation31.898276
Coefficient of variation (CV)0.57474371
Kurtosis-1.2
Mean55.5
Median Absolute Deviation (MAD)27.5
Skewness0
Sum6105
Variance1017.5
MonotonicityStrictly increasing
2023-12-12T18:37:35.968751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
71 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
Other values (100) 100
90.9%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%

시군명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size1012.0 B
태안군
30 
공주시
17 
아산시
11 
예산군
11 
보령시
10 
Other values (8)
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
태안군 30
27.3%
공주시 17
15.5%
아산시 11
 
10.0%
예산군 11
 
10.0%
보령시 10
 
9.1%
당진시 6
 
5.5%
청양군 6
 
5.5%
천안시 5
 
4.5%
논산시 4
 
3.6%
금산군 4
 
3.6%
Other values (3) 6
 
5.5%

Length

2023-12-12T18:37:36.134693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
태안군 30
27.3%
공주시 17
15.5%
아산시 11
 
10.0%
예산군 11
 
10.0%
보령시 10
 
9.1%
당진시 6
 
5.5%
청양군 6
 
5.5%
천안시 5
 
4.5%
논산시 4
 
3.6%
금산군 4
 
3.6%
Other values (3) 6
 
5.5%

업체명
Text

UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2023-12-12T18:37:36.360510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.8090909
Min length3

Characters and Unicode

Total characters969
Distinct characters195
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)100.0%

Sample

1st row 유성관광농원
2nd row 광덕산 관광농원
3rd row 아름다운 화수목 관광농원
4th row 풍세관광농원
5th row 광덕밤골관광농원
ValueCountFrequency (%)
관광농원 22
 
15.5%
농어촌관광농원 2
 
1.4%
칠갑산 1
 
0.7%
백화원 1
 
0.7%
예당수풀림관광농원 1
 
0.7%
백설농부관광농원 1
 
0.7%
예당관광농원 1
 
0.7%
광시관광농원 1
 
0.7%
아그로랜드관광농원 1
 
0.7%
푸른언덕관광농원 1
 
0.7%
Other values (110) 110
77.5%
2023-12-12T18:37:36.742869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
228
23.5%
86
 
8.9%
84
 
8.7%
79
 
8.2%
76
 
7.8%
12
 
1.2%
9
 
0.9%
8
 
0.8%
8
 
0.8%
8
 
0.8%
Other values (185) 371
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 737
76.1%
Space Separator 228
 
23.5%
Decimal Number 2
 
0.2%
Other Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
 
11.7%
84
 
11.4%
79
 
10.7%
76
 
10.3%
12
 
1.6%
9
 
1.2%
8
 
1.1%
8
 
1.1%
8
 
1.1%
7
 
0.9%
Other values (181) 360
48.8%
Space Separator
ValueCountFrequency (%)
228
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 738
76.2%
Common 231
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
 
11.7%
84
 
11.4%
79
 
10.7%
76
 
10.3%
12
 
1.6%
9
 
1.2%
8
 
1.1%
8
 
1.1%
8
 
1.1%
7
 
0.9%
Other values (182) 361
48.9%
Common
ValueCountFrequency (%)
228
98.7%
2 2
 
0.9%
, 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 737
76.1%
ASCII 231
 
23.8%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
228
98.7%
2 2
 
0.9%
, 1
 
0.4%
Hangul
ValueCountFrequency (%)
86
 
11.7%
84
 
11.4%
79
 
10.7%
76
 
10.3%
12
 
1.6%
9
 
1.2%
8
 
1.1%
8
 
1.1%
8
 
1.1%
7
 
0.9%
Other values (181) 360
48.8%
None
ValueCountFrequency (%)
1
100.0%
Distinct6
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1012.0 B
개인
56 
법인
20 
개인
16 
법인
개인
 
5

Length

Max length6
Median length4
Mean length3.7090909
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 개인
2nd row 개인
3rd row 개인
4th row 개인
5th row 법인

Common Values

ValueCountFrequency (%)
개인 56
50.9%
법인 20
 
18.2%
개인 16
 
14.5%
법인 9
 
8.2%
개인 5
 
4.5%
법인 4
 
3.6%

Length

2023-12-12T18:37:36.886673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:37:37.020808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 77
70.0%
법인 33
30.0%
Distinct107
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13130.5
Minimum2972
Maximum94275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T18:37:37.136181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2972
5-th percentile4081.7
Q14992.25
median7448
Q316408
95-th percentile32434.7
Maximum94275
Range91303
Interquartile range (IQR)11415.75

Descriptive statistics

Standard deviation13507.391
Coefficient of variation (CV)1.0287035
Kurtosis12.962015
Mean13130.5
Median Absolute Deviation (MAD)2546.5
Skewness3.0464066
Sum1444355
Variance1.8244962 × 108
MonotonicityNot monotonic
2023-12-12T18:37:37.306050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4950 2
 
1.8%
4900 2
 
1.8%
29500 2
 
1.8%
10806 1
 
0.9%
9840 1
 
0.9%
9895 1
 
0.9%
24435 1
 
0.9%
5842 1
 
0.9%
6374 1
 
0.9%
19982 1
 
0.9%
Other values (97) 97
88.2%
ValueCountFrequency (%)
2972 1
0.9%
3157 1
0.9%
3255 1
0.9%
3297 1
0.9%
3970 1
0.9%
3989 1
0.9%
4195 1
0.9%
4283 1
0.9%
4340 1
0.9%
4406 1
0.9%
ValueCountFrequency (%)
94275 1
0.9%
65626 1
0.9%
48272 1
0.9%
44794 1
0.9%
38297 1
0.9%
34520 1
0.9%
29886 1
0.9%
29868 1
0.9%
29794 1
0.9%
29500 2
1.8%
Distinct83
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2023-12-12T18:37:37.565998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length40
Mean length18.054545
Min length5

Characters and Unicode

Total characters1986
Distinct characters154
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)67.3%

Sample

1st row직판장, 집하장, 저장고, 수영장, 학습관
2nd row직판장, 식당, 풀장, 휴게실
3rd row직판장, 식당, 체험장
4th row영농체험시설, 수영장, 휴게실
5th row영농체험시설, 식당, 휴게실
ValueCountFrequency (%)
영농체험시설 47
 
12.8%
45
 
12.3%
숙박시설 27
 
7.4%
야영장 23
 
6.3%
체험농지 21
 
5.7%
소매점 16
 
4.4%
수영장 12
 
3.3%
음식점 11
 
3.0%
식당 9
 
2.5%
농산물판매장 6
 
1.6%
Other values (115) 150
40.9%
2023-12-12T18:37:37.960540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
287
 
14.5%
, 202
 
10.2%
97
 
4.9%
97
 
4.9%
94
 
4.7%
94
 
4.7%
93
 
4.7%
90
 
4.5%
89
 
4.5%
53
 
2.7%
Other values (144) 790
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1352
68.1%
Space Separator 287
 
14.5%
Other Punctuation 215
 
10.8%
Decimal Number 101
 
5.1%
Other Symbol 19
 
1.0%
Open Punctuation 6
 
0.3%
Close Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
97
 
7.2%
97
 
7.2%
94
 
7.0%
94
 
7.0%
93
 
6.9%
90
 
6.7%
89
 
6.6%
53
 
3.9%
39
 
2.9%
35
 
2.6%
Other values (127) 571
42.2%
Decimal Number
ValueCountFrequency (%)
2 20
19.8%
0 18
17.8%
5 16
15.8%
1 14
13.9%
4 9
8.9%
7 7
 
6.9%
3 6
 
5.9%
6 6
 
5.9%
9 3
 
3.0%
8 2
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 202
94.0%
. 8
 
3.7%
: 5
 
2.3%
Space Separator
ValueCountFrequency (%)
287
100.0%
Other Symbol
ValueCountFrequency (%)
19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1352
68.1%
Common 634
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
97
 
7.2%
97
 
7.2%
94
 
7.0%
94
 
7.0%
93
 
6.9%
90
 
6.7%
89
 
6.6%
53
 
3.9%
39
 
2.9%
35
 
2.6%
Other values (127) 571
42.2%
Common
ValueCountFrequency (%)
287
45.3%
, 202
31.9%
2 20
 
3.2%
19
 
3.0%
0 18
 
2.8%
5 16
 
2.5%
1 14
 
2.2%
4 9
 
1.4%
. 8
 
1.3%
7 7
 
1.1%
Other values (7) 34
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1352
68.1%
ASCII 615
31.0%
CJK Compat 19
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
287
46.7%
, 202
32.8%
2 20
 
3.3%
0 18
 
2.9%
5 16
 
2.6%
1 14
 
2.3%
4 9
 
1.5%
. 8
 
1.3%
7 7
 
1.1%
( 6
 
1.0%
Other values (6) 28
 
4.6%
Hangul
ValueCountFrequency (%)
97
 
7.2%
97
 
7.2%
94
 
7.0%
94
 
7.0%
93
 
6.9%
90
 
6.7%
89
 
6.6%
53
 
3.9%
39
 
2.9%
35
 
2.6%
Other values (127) 571
42.2%
CJK Compat
ValueCountFrequency (%)
19
100.0%

Interactions

2023-12-12T18:37:34.960405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:37:34.774318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:37:35.045196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:37:34.868920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:37:38.060680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군명유형(개인_법인)농원면적(제곱미터)농원 주요시설
연번1.0000.9280.6920.1320.970
시군명0.9281.0000.6340.2790.998
유형(개인_법인)0.6920.6341.0000.0000.000
농원면적(제곱미터)0.1320.2790.0001.0000.964
농원 주요시설0.9700.9980.0000.9641.000
2023-12-12T18:37:38.156718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형(개인_법인)시군명
유형(개인_법인)1.0000.364
시군명0.3641.000
2023-12-12T18:37:38.251629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번농원면적(제곱미터)시군명유형(개인_법인)
연번1.000-0.0500.7300.446
농원면적(제곱미터)-0.0501.0000.1170.000
시군명0.7300.1171.0000.364
유형(개인_법인)0.4460.0000.3641.000

Missing values

2023-12-12T18:37:35.477418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:37:35.613422image/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

연번시군명업체명유형(개인_법인)농원면적(제곱미터)농원 주요시설
01천안시유성관광농원개인10806직판장, 집하장, 저장고, 수영장, 학습관
12천안시광덕산 관광농원개인3297직판장, 식당, 풀장, 휴게실
23천안시아름다운 화수목 관광농원개인28654직판장, 식당, 체험장
34천안시풍세관광농원개인4836영농체험시설, 수영장, 휴게실
45천안시광덕밤골관광농원법인7257영농체험시설, 식당, 휴게실
56공주시은적골개인4975영농체험시설, 숙박시설, 소매점 등
67공주시정안장자울개인17197영농체험시설, 숙소, 창고 등
78공주시구왕대개인8339영농체험시설, 야영장 등
89공주시울가족개인8968영농체험시설, 농산물판매점
910공주시공주개인3970영농체험시설, 물놀이시설
연번시군명업체명유형(개인_법인)농원면적(제곱미터)농원 주요시설
100101태안군안면도자연휴양림마을법인4645체험농지, 음식점, 제조업소 등
101102태안군만리포솔향기법인15463영농체험시설, 야영장 등
102103태안군송림관광농원법인5219영농체험시설, 야영장 등
103104태안군여름과 소나무관광농원법인5960숙박시설, 체험농지
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