Overview

Dataset statistics

Number of variables13
Number of observations1146
Missing cells5536
Missing cells (%)37.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory124.4 KiB
Average record size in memory111.1 B

Variable types

Numeric5
DateTime3
Boolean1
Text2
Categorical1
Unsupported1

Dataset

Description충북농업기술원 농가 경영기록장 "바로바로"의 농업회계분석 정보제공 관련 자산, 부채, 감가상각비 등 계정과목 관리시스템으로 일련번호, 자산일련번호, 등록일시, 수정일시, 상태, 규격, 면적(평), 설치일시, 감가상각액, 계정과목코드, 차변전표일련번호, 대변전표일련번호, 비고등을 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050294/fileData.do

Alerts

상태 has constant value ""Constant
일련번호 is highly overall correlated with 자산일련번호 and 1 other fieldsHigh correlation
자산일련번호 is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
감가상각액 is highly overall correlated with 자산일련번호 and 1 other fieldsHigh correlation
차변전표일련번호 is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
계정과목코드 is highly overall correlated with 자산일련번호High correlation
규격 has 918 (80.1%) missing valuesMissing
면적(평) has 853 (74.4%) missing valuesMissing
감가상각액 has 1133 (98.9%) missing valuesMissing
차변전표일련번호 has 811 (70.8%) missing valuesMissing
대변전표일련번호 has 1146 (100.0%) missing valuesMissing
비고 has 674 (58.8%) missing valuesMissing
일련번호 has unique valuesUnique
대변전표일련번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 17:52:32.827439
Analysis finished2023-12-12 17:52:36.983512
Duration4.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1146
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2370.4572
Minimum11
Maximum4000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-13T02:52:37.095966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile212.25
Q11241.5
median2504.5
Q33687.75
95-th percentile3936.75
Maximum4000
Range3989
Interquartile range (IQR)2446.25

Descriptive statistics

Standard deviation1281.7411
Coefficient of variation (CV)0.54071472
Kurtosis-1.3018608
Mean2370.4572
Median Absolute Deviation (MAD)1194
Skewness-0.31197334
Sum2716544
Variance1642860.3
MonotonicityStrictly increasing
2023-12-13T02:52:37.302391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 1
 
0.1%
3322 1
 
0.1%
3345 1
 
0.1%
3341 1
 
0.1%
3337 1
 
0.1%
3336 1
 
0.1%
3328 1
 
0.1%
3327 1
 
0.1%
3320 1
 
0.1%
3348 1
 
0.1%
Other values (1136) 1136
99.1%
ValueCountFrequency (%)
11 1
0.1%
18 1
0.1%
25 1
0.1%
38 1
0.1%
40 1
0.1%
41 1
0.1%
42 1
0.1%
48 1
0.1%
50 1
0.1%
52 1
0.1%
ValueCountFrequency (%)
4000 1
0.1%
3999 1
0.1%
3998 1
0.1%
3997 1
0.1%
3996 1
0.1%
3995 1
0.1%
3994 1
0.1%
3993 1
0.1%
3992 1
0.1%
3991 1
0.1%

자산일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212.637
Minimum200
Maximum464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-13T02:52:37.507190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile200
Q1200
median201
Q3203
95-th percentile245
Maximum464
Range264
Interquartile range (IQR)3

Descriptive statistics

Standard deviation35.243866
Coefficient of variation (CV)0.16574663
Kurtosis29.856969
Mean212.637
Median Absolute Deviation (MAD)1
Skewness5.2334351
Sum243682
Variance1242.1301
MonotonicityNot monotonic
2023-12-13T02:52:37.738503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
200 400
34.9%
201 287
25.0%
202 130
 
11.3%
234 73
 
6.4%
203 59
 
5.1%
245 38
 
3.3%
221 34
 
3.0%
232 21
 
1.8%
246 16
 
1.4%
228 8
 
0.7%
Other values (31) 80
 
7.0%
ValueCountFrequency (%)
200 400
34.9%
201 287
25.0%
202 130
 
11.3%
203 59
 
5.1%
204 3
 
0.3%
206 2
 
0.2%
209 1
 
0.1%
210 1
 
0.1%
211 1
 
0.1%
215 1
 
0.1%
ValueCountFrequency (%)
464 1
 
0.1%
434 6
 
0.5%
433 7
 
0.6%
432 3
 
0.3%
431 4
 
0.3%
430 3
 
0.3%
248 1
 
0.1%
247 1
 
0.1%
246 16
1.4%
245 38
3.3%

등록일시
Date

Distinct298
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
Minimum1900-01-01 00:00:00
Maximum2019-11-05 09:41:00
2023-12-13T02:52:38.011781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:38.261348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

Distinct303
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
Minimum1900-01-01 00:00:00
Maximum2019-11-05 09:41:00
2023-12-13T02:52:38.428408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:38.569993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상태
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
False
1146 
ValueCountFrequency (%)
False 1146
100.0%
2023-12-13T02:52:38.711383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

규격
Text

MISSING 

Distinct197
Distinct (%)86.4%
Missing918
Missing (%)80.1%
Memory size9.1 KiB
2023-12-13T02:52:38.979154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length29
Mean length5.8070175
Min length1

Characters and Unicode

Total characters1324
Distinct characters161
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)78.5%

Sample

1st row폭 7m * 길이 20m
2nd row3m*7m*2m*2홀
3rd row2.5HP
4th row45*7.2
5th row67평방미터
ValueCountFrequency (%)
3평 7
 
2.3%
5평 6
 
2.0%
비닐연동하우스 4
 
1.3%
파이프 4
 
1.3%
l90m 3
 
1.0%
7m 3
 
1.0%
60평 3
 
1.0%
폭.길이 3
 
1.0%
× 3
 
1.0%
30평 3
 
1.0%
Other values (231) 261
87.0%
2023-12-13T02:52:39.535705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 143
 
10.8%
89
 
6.7%
5 85
 
6.4%
m 81
 
6.1%
1 74
 
5.6%
평 60
 
4.5%
3 57
 
4.3%
2 56
 
4.2%
동 52
 
3.9%
× 34
 
2.6%
Other values (151) 593
44.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 527
39.8%
Other Letter 466
35.2%
Lowercase Letter 100
 
7.6%
Space Separator 89
 
6.7%
Other Punctuation 70
 
5.3%
Math Symbol 36
 
2.7%
Uppercase Letter 14
 
1.1%
Open Punctuation 9
 
0.7%
Close Punctuation 9
 
0.7%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 60
 
12.9%
동 52
 
11.2%
스 15
 
3.2%
연 15
 
3.2%
우 15
 
3.2%
이 14
 
3.0%
하 13
 
2.8%
비 13
 
2.8%
개 12
 
2.6%
닐 9
 
1.9%
Other values (112) 248
53.2%
Lowercase Letter
ValueCountFrequency (%)
m 81
81.0%
c 3
 
3.0%
x 3
 
3.0%
w 3
 
3.0%
h 3
 
3.0%
l 2
 
2.0%
t 1
 
1.0%
a 1
 
1.0%
k 1
 
1.0%
y 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
0 143
27.1%
5 85
16.1%
1 74
14.0%
3 57
 
10.8%
2 56
 
10.6%
6 32
 
6.1%
4 25
 
4.7%
8 21
 
4.0%
7 18
 
3.4%
9 16
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
L 4
28.6%
H 4
28.6%
W 3
21.4%
C 1
 
7.1%
B 1
 
7.1%
P 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 31
44.3%
* 23
32.9%
, 14
20.0%
/ 1
 
1.4%
; 1
 
1.4%
Math Symbol
ValueCountFrequency (%)
× 34
94.4%
~ 1
 
2.8%
= 1
 
2.8%
Space Separator
ValueCountFrequency (%)
89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 744
56.2%
Hangul 466
35.2%
Latin 114
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 60
 
12.9%
동 52
 
11.2%
스 15
 
3.2%
연 15
 
3.2%
우 15
 
3.2%
이 14
 
3.0%
하 13
 
2.8%
비 13
 
2.8%
개 12
 
2.6%
닐 9
 
1.9%
Other values (112) 248
53.2%
Common
ValueCountFrequency (%)
0 143
19.2%
89
12.0%
5 85
11.4%
1 74
9.9%
3 57
 
7.7%
2 56
 
7.5%
× 34
 
4.6%
6 32
 
4.3%
. 31
 
4.2%
4 25
 
3.4%
Other values (12) 118
15.9%
Latin
ValueCountFrequency (%)
m 81
71.1%
L 4
 
3.5%
H 4
 
3.5%
W 3
 
2.6%
c 3
 
2.6%
x 3
 
2.6%
w 3
 
2.6%
h 3
 
2.6%
l 2
 
1.8%
t 1
 
0.9%
Other values (7) 7
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 824
62.2%
Hangul 465
35.1%
None 34
 
2.6%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143
17.4%
89
10.8%
5 85
10.3%
m 81
9.8%
1 74
9.0%
3 57
 
6.9%
2 56
 
6.8%
6 32
 
3.9%
. 31
 
3.8%
4 25
 
3.0%
Other values (28) 151
18.3%
Hangul
ValueCountFrequency (%)
평 60
 
12.9%
동 52
 
11.2%
스 15
 
3.2%
연 15
 
3.2%
우 15
 
3.2%
이 14
 
3.0%
하 13
 
2.8%
비 13
 
2.8%
개 12
 
2.6%
닐 9
 
1.9%
Other values (111) 247
53.1%
None
ValueCountFrequency (%)
× 34
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

면적(평)
Real number (ℝ)

MISSING 

Distinct112
Distinct (%)38.2%
Missing853
Missing (%)74.4%
Infinite0
Infinite (%)0.0%
Mean885.32423
Minimum0
Maximum33000
Zeros4
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-13T02:52:39.725239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q120
median120
Q3900
95-th percentile3300
Maximum33000
Range33000
Interquartile range (IQR)880

Descriptive statistics

Standard deviation2411.1821
Coefficient of variation (CV)2.7235018
Kurtosis109.70455
Mean885.32423
Median Absolute Deviation (MAD)117
Skewness8.9758504
Sum259400
Variance5813799.2
MonotonicityNot monotonic
2023-12-13T02:52:39.907172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 15
 
1.3%
3 14
 
1.2%
100 13
 
1.1%
5 11
 
1.0%
50 11
 
1.0%
600 10
 
0.9%
1000 10
 
0.9%
1 9
 
0.8%
200 8
 
0.7%
10 7
 
0.6%
Other values (102) 185
 
16.1%
(Missing) 853
74.4%
ValueCountFrequency (%)
0 4
 
0.3%
1 9
0.8%
2 1
 
0.1%
3 14
1.2%
4 3
 
0.3%
5 11
1.0%
6 7
0.6%
7 1
 
0.1%
8 2
 
0.2%
9 3
 
0.3%
ValueCountFrequency (%)
33000 1
0.1%
10046 2
0.2%
9052 1
0.1%
8000 2
0.2%
6080 1
0.1%
6000 1
0.1%
5040 1
0.1%
5000 1
0.1%
4000 1
0.1%
3904 1
0.1%

설치일
Date

Distinct844
Distinct (%)73.7%
Missing1
Missing (%)0.1%
Memory size9.1 KiB
Minimum1900-01-01 00:00:00
Maximum2020-06-20 00:00:00
2023-12-13T02:52:40.162973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:40.367645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

감가상각액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)92.3%
Missing1133
Missing (%)98.9%
Infinite0
Infinite (%)0.0%
Mean803471.08
Minimum0
Maximum4000000
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-13T02:52:40.520219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114
median300000
Q3875000
95-th percentile3148000
Maximum4000000
Range4000000
Interquartile range (IQR)874986

Descriptive statistics

Standard deviation1228134.4
Coefficient of variation (CV)1.5285359
Kurtosis3.1670737
Mean803471.08
Median Absolute Deviation (MAD)299990
Skewness1.9014424
Sum10445124
Variance1.5083142 × 1012
MonotonicityNot monotonic
2023-12-13T02:52:40.672695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 2
 
0.2%
2580000 1
 
0.1%
450000 1
 
0.1%
300000 1
 
0.1%
10 1
 
0.1%
240000 1
 
0.1%
1600000 1
 
0.1%
400000 1
 
0.1%
14 1
 
0.1%
100 1
 
0.1%
Other values (2) 2
 
0.2%
(Missing) 1133
98.9%
ValueCountFrequency (%)
0 2
0.2%
10 1
0.1%
14 1
0.1%
100 1
0.1%
240000 1
0.1%
300000 1
0.1%
400000 1
0.1%
450000 1
0.1%
875000 1
0.1%
1600000 1
0.1%
ValueCountFrequency (%)
4000000 1
0.1%
2580000 1
0.1%
1600000 1
0.1%
875000 1
0.1%
450000 1
0.1%
400000 1
0.1%
300000 1
0.1%
240000 1
0.1%
100 1
0.1%
14 1
0.1%

계정과목코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
<NA>
811 
158
312 
156
 
23

Length

Max length4
Median length4
Mean length3.7076789
Min length3

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> 811
70.8%
158 312
 
27.2%
156 23
 
2.0%

Length

2023-12-13T02:52:40.851614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:40.977374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 811
70.8%
158 312
 
27.2%
156 23
 
2.0%

차변전표일련번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct335
Distinct (%)100.0%
Missing811
Missing (%)70.8%
Infinite0
Infinite (%)0.0%
Mean791554.5
Minimum713068
Maximum876632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2023-12-13T02:52:41.472403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum713068
5-th percentile715449.4
Q1748015
median779849
Q3853667.5
95-th percentile874462.1
Maximum876632
Range163564
Interquartile range (IQR)105652.5

Descriptive statistics

Standard deviation54876.253
Coefficient of variation (CV)0.069327195
Kurtosis-1.4096795
Mean791554.5
Median Absolute Deviation (MAD)49287
Skewness0.16585008
Sum2.6517076 × 108
Variance3.0114032 × 109
MonotonicityNot monotonic
2023-12-13T02:52:41.653417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
815633 1
 
0.1%
817279 1
 
0.1%
816664 1
 
0.1%
816662 1
 
0.1%
816266 1
 
0.1%
816264 1
 
0.1%
816262 1
 
0.1%
816206 1
 
0.1%
816204 1
 
0.1%
814857 1
 
0.1%
Other values (325) 325
28.4%
(Missing) 811
70.8%
ValueCountFrequency (%)
713068 1
0.1%
713070 1
0.1%
713077 1
0.1%
713081 1
0.1%
713404 1
0.1%
715196 1
0.1%
715198 1
0.1%
715202 1
0.1%
715204 1
0.1%
715206 1
0.1%
ValueCountFrequency (%)
876632 1
0.1%
876371 1
0.1%
876112 1
0.1%
876109 1
0.1%
874971 1
0.1%
874968 1
0.1%
874956 1
0.1%
874954 1
0.1%
874951 1
0.1%
874797 1
0.1%

대변전표일련번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1146
Missing (%)100.0%
Memory size10.2 KiB

비고
Text

MISSING 

Distinct451
Distinct (%)95.6%
Missing674
Missing (%)58.8%
Memory size9.1 KiB
2023-12-13T02:52:42.001444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length49
Mean length10.17161
Min length2

Characters and Unicode

Total characters4801
Distinct characters431
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique437 ?
Unique (%)92.6%

Sample

1st row지초하우스
2nd row하우스설치비 9동
3rd row연동 15동, 단동 10동, 육묘장 1동
4th row냉장겸용 3칸(그랜드코리아)
5th row보조40%
ValueCountFrequency (%)
설치 15
 
1.6%
및 12
 
1.3%
하우스 9
 
1.0%
포함 8
 
0.9%
작업장 7
 
0.8%
비닐하우스 7
 
0.8%
창고 6
 
0.7%
기타 6
 
0.7%
5평 6
 
0.7%
시설 5
 
0.5%
Other values (726) 838
91.2%
2023-12-13T02:52:42.517385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
469
 
9.8%
0 342
 
7.1%
1 126
 
2.6%
2 116
 
2.4%
5 85
 
1.8%
, 85
 
1.8%
동 84
 
1.7%
평 77
 
1.6%
스 71
 
1.5%
설 70
 
1.5%
Other values (421) 3276
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3025
63.0%
Decimal Number 929
 
19.4%
Space Separator 469
 
9.8%
Other Punctuation 192
 
4.0%
Lowercase Letter 54
 
1.1%
Close Punctuation 45
 
0.9%
Open Punctuation 29
 
0.6%
Math Symbol 27
 
0.6%
Uppercase Letter 16
 
0.3%
Dash Punctuation 14
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 84
 
2.8%
평 77
 
2.5%
스 71
 
2.3%
설 70
 
2.3%
기 67
 
2.2%
비 64
 
2.1%
사 63
 
2.1%
하 62
 
2.0%
원 61
 
2.0%
우 60
 
2.0%
Other values (370) 2346
77.6%
Lowercase Letter
ValueCountFrequency (%)
m 21
38.9%
n 5
 
9.3%
t 4
 
7.4%
a 4
 
7.4%
u 3
 
5.6%
o 3
 
5.6%
c 3
 
5.6%
x 2
 
3.7%
y 1
 
1.9%
d 1
 
1.9%
Other values (7) 7
 
13.0%
Decimal Number
ValueCountFrequency (%)
0 342
36.8%
1 126
 
13.6%
2 116
 
12.5%
5 85
 
9.1%
3 69
 
7.4%
6 55
 
5.9%
4 45
 
4.8%
7 37
 
4.0%
8 30
 
3.2%
9 24
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
M 3
18.8%
J 3
18.8%
S 2
12.5%
V 2
12.5%
A 2
12.5%
T 2
12.5%
L 1
 
6.2%
B 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 85
44.3%
. 65
33.9%
% 17
 
8.9%
/ 12
 
6.2%
* 7
 
3.6%
: 5
 
2.6%
; 1
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 10
37.0%
+ 8
29.6%
× 7
25.9%
= 2
 
7.4%
Space Separator
ValueCountFrequency (%)
469
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3025
63.0%
Common 1706
35.5%
Latin 70
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 84
 
2.8%
평 77
 
2.5%
스 71
 
2.3%
설 70
 
2.3%
기 67
 
2.2%
비 64
 
2.1%
사 63
 
2.1%
하 62
 
2.0%
원 61
 
2.0%
우 60
 
2.0%
Other values (370) 2346
77.6%
Common
ValueCountFrequency (%)
469
27.5%
0 342
20.0%
1 126
 
7.4%
2 116
 
6.8%
5 85
 
5.0%
, 85
 
5.0%
3 69
 
4.0%
. 65
 
3.8%
6 55
 
3.2%
4 45
 
2.6%
Other values (16) 249
14.6%
Latin
ValueCountFrequency (%)
m 21
30.0%
n 5
 
7.1%
t 4
 
5.7%
a 4
 
5.7%
M 3
 
4.3%
u 3
 
4.3%
o 3
 
4.3%
c 3
 
4.3%
J 3
 
4.3%
S 2
 
2.9%
Other values (15) 19
27.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3024
63.0%
ASCII 1769
36.8%
None 7
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
469
26.5%
0 342
19.3%
1 126
 
7.1%
2 116
 
6.6%
5 85
 
4.8%
, 85
 
4.8%
3 69
 
3.9%
. 65
 
3.7%
6 55
 
3.1%
4 45
 
2.5%
Other values (40) 312
17.6%
Hangul
ValueCountFrequency (%)
동 84
 
2.8%
평 77
 
2.5%
스 71
 
2.3%
설 70
 
2.3%
기 67
 
2.2%
비 64
 
2.1%
사 63
 
2.1%
하 62
 
2.1%
원 61
 
2.0%
우 60
 
2.0%
Other values (369) 2345
77.5%
None
ValueCountFrequency (%)
× 7
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 1
100.0%

Interactions

2023-12-13T02:52:35.825484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:33.426139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:34.012879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:34.551349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.294475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.932228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:33.529829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:34.115151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:34.655146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.383753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:36.059628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:33.637847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:34.206522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.009310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.478906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:36.186859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:33.752056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:34.304495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.096819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.587614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:36.308294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:33.861930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:34.412369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.192521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:35.685253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:52:42.649825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호자산일련번호면적(평)감가상각액계정과목코드차변전표일련번호
일련번호1.0000.2800.0001.0000.0000.205
자산일련번호0.2801.0000.0000.8881.0000.000
면적(평)0.0000.0001.000NaN0.0000.300
감가상각액1.0000.888NaN1.0000.0000.000
계정과목코드0.0001.0000.0000.0001.0000.000
차변전표일련번호0.2050.0000.3000.0000.0001.000
2023-12-13T02:52:42.804812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호자산일련번호면적(평)감가상각액차변전표일련번호계정과목코드
일련번호1.0000.6800.0440.1320.8920.000
자산일련번호0.6801.000-0.355-0.506-0.1290.997
면적(평)0.044-0.3551.000-0.2000.0950.000
감가상각액0.132-0.506-0.2001.0000.5860.000
차변전표일련번호0.892-0.1290.0950.5861.0000.000
계정과목코드0.0000.9970.0000.0000.0001.000

Missing values

2023-12-13T02:52:36.481236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:52:36.653115image/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.
2023-12-13T02:52:36.845870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

일련번호자산일련번호등록일시수정일시상태규격면적(평)설치일감가상각액계정과목코드차변전표일련번호대변전표일련번호비고
0112001900-01-01 00:001900-01-01 00:00N<NA><NA>2010-07-28<NA><NA><NA><NA><NA>
1182001900-01-01 00:001900-01-01 00:00N<NA><NA>2013-04-29<NA><NA><NA><NA>지초하우스
2252001900-01-01 00:001900-01-01 00:00N<NA><NA>2009-07-30<NA><NA><NA><NA><NA>
3382001900-01-01 00:001900-01-01 00:00N<NA><NA>2012-05-30<NA><NA><NA><NA>하우스설치비 9동
4402001900-01-01 00:001900-01-01 00:00N<NA><NA>2006-06-30<NA><NA><NA><NA><NA>
5412001900-01-01 00:001900-01-01 00:00N<NA><NA>2008-03-30<NA><NA><NA><NA><NA>
6422001900-01-01 00:001900-01-01 00:00N<NA><NA>2011-07-31<NA><NA><NA><NA><NA>
7482001900-01-01 00:001900-01-01 00:00N<NA><NA>2011-07-31<NA><NA><NA><NA><NA>
8502001900-01-01 00:001900-01-01 00:00N<NA><NA>2011-01-01<NA><NA><NA><NA>연동 15동, 단동 10동, 육묘장 1동
9522001900-01-01 00:001900-01-01 00:00N<NA><NA>2012-06-01<NA><NA><NA><NA>냉장겸용 3칸(그랜드코리아)
일련번호자산일련번호등록일시수정일시상태규격면적(평)설치일감가상각액계정과목코드차변전표일련번호대변전표일련번호비고
113639912012019-10-30 14:232019-10-30 14:23N연동2002019-10-30<NA>158874453<NA><NA>
113739922012019-10-30 14:232019-10-30 14:23N단독1002019-03-30<NA>158874455<NA><NA>
113839932012019-10-30 14:252019-10-30 14:25N200*631602019-02-28<NA>158874460<NA><NA>
113939942212019-10-30 14:292019-10-30 14:29N5*5<NA>2004-10-30<NA>158874471<NA><NA>
114039952012019-10-30 16:122019-10-30 19:32N양액시설비6902017-09-15<NA>158874791<NA><NA>
114139962012019-10-30 19:242019-11-03 19:27N작업장(방,화장실)502018-01-01<NA>158876112<NA><NA>
114239972012019-10-30 19:412019-11-03 19:27N체험장502019-10-30<NA>158876109<NA><NA>
114339982012019-10-30 23:272019-10-30 23:27N양액시설6502019-09-01<NA>158874968<NA><NA>
114439994642019-11-05 09:162019-11-05 09:16N<NA><NA>2019-03-21<NA>158876371<NA>보조등 써비스
114540002012019-11-05 09:412019-11-05 09:41N1.2중비닐교채(1,3동) 2중비닐교채(2동)수막물받이3동6902019-10-05<NA>158876632<NA><NA>