Overview

Dataset statistics

Number of variables12
Number of observations98
Missing cells654
Missing cells (%)55.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory98.3 B

Variable types

Text8
Numeric1
Categorical3

Dataset

Description통계청홈페이지 통계조사 메타 데이터
Author통계청
URLhttps://www.data.go.kr/data/15071740/fileData.do

Alerts

순번 is highly overall correlated with 방식High correlation
방식 is highly overall correlated with 순번High correlation
방식 is highly imbalanced (72.7%)Imbalance
요약정보 has 95 (96.9%) missing valuesMissing
이미지설명글 has 79 (80.6%) missing valuesMissing
키워드1 has 96 (98.0%) missing valuesMissing
키워드2 has 96 (98.0%) missing valuesMissing
키워드3 has 96 (98.0%) missing valuesMissing
키워드4 has 96 (98.0%) missing valuesMissing
키워드5 has 96 (98.0%) missing valuesMissing
순번 has 1 (1.0%) zerosZeros

Reproduction

Analysis started2023-12-12 07:01:46.026668
Analysis finished2023-12-12 07:01:47.132683
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제목
Text

Distinct96
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-12T16:01:47.298674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.8061224
Min length2

Characters and Unicode

Total characters667
Distinct characters142
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

Unique94 ?
Unique (%)95.9%

Sample

1st row조사분류
2nd row인구·가구
3rd row인구총조사
4th row인구동향조사
5th row국내인구이동통계
ValueCountFrequency (%)
퇴직연금통계 2
 
2.0%
농가판매및구입가격조사 2
 
2.0%
경제총조사 2
 
2.0%
국민이전계정 1
 
1.0%
이민자체류실태및고용조사 1
 
1.0%
양곡소비량조사 1
 
1.0%
농업면적조사 1
 
1.0%
대기배출계정 1
 
1.0%
주택소유통계 1
 
1.0%
산지쌀값조사 1
 
1.0%
Other values (87) 87
87.0%
2023-12-12T16:01:47.600924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 62
 
9.3%
조 59
 
8.8%
업 32
 
4.8%
계 27
 
4.0%
동 17
 
2.5%
통 16
 
2.4%
가 15
 
2.2%
인 15
 
2.2%
농 13
 
1.9%
향 12
 
1.8%
Other values (132) 399
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 645
96.7%
Other Punctuation 11
 
1.6%
Space Separator 9
 
1.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 62
 
9.6%
조 59
 
9.1%
업 32
 
5.0%
계 27
 
4.2%
동 17
 
2.6%
통 16
 
2.5%
가 15
 
2.3%
인 15
 
2.3%
농 13
 
2.0%
향 12
 
1.9%
Other values (128) 377
58.4%
Other Punctuation
ValueCountFrequency (%)
· 11
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 645
96.7%
Common 22
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 62
 
9.6%
조 59
 
9.1%
업 32
 
5.0%
계 27
 
4.2%
동 17
 
2.6%
통 16
 
2.5%
가 15
 
2.3%
인 15
 
2.3%
농 13
 
2.0%
향 12
 
1.9%
Other values (128) 377
58.4%
Common
ValueCountFrequency (%)
· 11
50.0%
9
40.9%
( 1
 
4.5%
) 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 645
96.7%
None 11
 
1.6%
ASCII 11
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 62
 
9.6%
조 59
 
9.1%
업 32
 
5.0%
계 27
 
4.2%
동 17
 
2.6%
통 16
 
2.5%
가 15
 
2.3%
인 15
 
2.3%
농 13
 
2.0%
향 12
 
1.9%
Other values (128) 377
58.4%
None
ValueCountFrequency (%)
· 11
100.0%
ASCII
ValueCountFrequency (%)
9
81.8%
( 1
 
9.1%
) 1
 
9.1%

순번
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7040816
Minimum0
Maximum19
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-12T16:01:47.699121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median5
Q38
95-th percentile14.15
Maximum19
Range19
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.3841542
Coefficient of variation (CV)0.76859948
Kurtosis0.55803344
Mean5.7040816
Median Absolute Deviation (MAD)3
Skewness1.0299239
Sum559
Variance19.220808
MonotonicityNot monotonic
2023-12-12T16:01:47.804006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 16
16.3%
3 11
11.2%
2 11
11.2%
4 9
9.2%
5 8
8.2%
6 7
7.1%
8 6
 
6.1%
7 6
 
6.1%
9 5
 
5.1%
10 5
 
5.1%
Other values (10) 14
14.3%
ValueCountFrequency (%)
0 1
 
1.0%
1 16
16.3%
2 11
11.2%
3 11
11.2%
4 9
9.2%
5 8
8.2%
6 7
7.1%
7 6
 
6.1%
8 6
 
6.1%
9 5
 
5.1%
ValueCountFrequency (%)
19 1
 
1.0%
18 1
 
1.0%
17 1
 
1.0%
16 1
 
1.0%
15 1
 
1.0%
14 2
 
2.0%
13 2
 
2.0%
12 2
 
2.0%
11 2
 
2.0%
10 5
5.1%

조사주기
Categorical

Distinct6
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size916.0 B
<NA>
73 
연간
11 
5년
8 
월간
 
3
분기
 
2

Length

Max length4
Median length4
Mean length3.4897959
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row5년
3rd row5년
4th row월간
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 73
74.5%
연간 11
 
11.2%
5년 8
 
8.2%
월간 3
 
3.1%
분기 2
 
2.0%
순기 1
 
1.0%

Length

2023-12-12T16:01:47.923091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:01:48.031358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 73
74.5%
연간 11
 
11.2%
5년 8
 
8.2%
월간 3
 
3.1%
분기 2
 
2.0%
순기 1
 
1.0%

방식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size916.0 B
<NA>
91 
가공통계
 
5
조사통계 > 전수조사
 
2

Length

Max length11
Median length4
Mean length4.1428571
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 91
92.9%
가공통계 5
 
5.1%
조사통계 > 전수조사 2
 
2.0%

Length

2023-12-12T16:01:48.176057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:01:48.325300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 91
89.2%
가공통계 5
 
4.9%
조사통계 2
 
2.0%
2
 
2.0%
전수조사 2
 
2.0%

요약정보
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing95
Missing (%)96.9%
Memory size916.0 B
2023-12-12T16:01:48.547645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length183
Median length137
Mean length136
Min length88

Characters and Unicode

Total characters408
Distinct characters119
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row우리나라의 모든 인구와 주택의 총수는 물론 개별 특성까지 파악하여 각종 경제 사회 발전계획의 수립 및 평가와 각종 학술연구, 민간부문의 경영계획수립에 활용하기 위해 실시하는 전국적 규모의 통계조사입니다. 이 조사는 지정통계 제1호(인구총조사)와 제2호(주택총조사)로 지정되어 있는 나라살림의 바탕이 되는 국가기본통계조사입니다.
2nd row농림어가 정의에 해당하는 전국의 모든 농가, 임가, 어가의 총수는 물론 개별 특성까지 파악하여 농림어업 정책 및 농산어촌 지역개발계획 수립 및 평가, 각종 학술연구 자료와 표본조사의 표본 틀로 활용하기 위해 실시하는 전국적 규모의 통계조사입니다.
3rd row대기오염 배출통계와 경제통계를 통합하여 작성하는 계정으로, 경제활동과 대기오염 간의 관계 및 파급효과를 분석하여 환경정책 운영에 필수적인 정보를 제공하기 위함
ValueCountFrequency (%)
및 4
 
4.5%
각종 3
 
3.4%
수립 2
 
2.2%
통계조사입니다 2
 
2.2%
규모의 2
 
2.2%
전국적 2
 
2.2%
대기오염 2
 
2.2%
위해 2
 
2.2%
활용하기 2
 
2.2%
모든 2
 
2.2%
Other values (59) 66
74.2%
2023-12-12T16:01:49.012813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
21.1%
의 12
 
2.9%
계 11
 
2.7%
하 11
 
2.7%
는 9
 
2.2%
사 8
 
2.0%
가 7
 
1.7%
조 7
 
1.7%
통 7
 
1.7%
정 7
 
1.7%
Other values (109) 243
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 307
75.2%
Space Separator 86
 
21.1%
Other Punctuation 8
 
2.0%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%
Decimal Number 2
 
0.5%
Control 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 12
 
3.9%
계 11
 
3.6%
하 11
 
3.6%
는 9
 
2.9%
사 8
 
2.6%
가 7
 
2.3%
조 7
 
2.3%
통 7
 
2.3%
정 7
 
2.3%
제 6
 
2.0%
Other values (101) 222
72.3%
Other Punctuation
ValueCountFrequency (%)
, 5
62.5%
. 3
37.5%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 307
75.2%
Common 101
 
24.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 12
 
3.9%
계 11
 
3.6%
하 11
 
3.6%
는 9
 
2.9%
사 8
 
2.6%
가 7
 
2.3%
조 7
 
2.3%
통 7
 
2.3%
정 7
 
2.3%
제 6
 
2.0%
Other values (101) 222
72.3%
Common
ValueCountFrequency (%)
86
85.1%
, 5
 
5.0%
. 3
 
3.0%
) 2
 
2.0%
( 2
 
2.0%
1
 
1.0%
1 1
 
1.0%
2 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 307
75.2%
ASCII 101
 
24.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
85.1%
, 5
 
5.0%
. 3
 
3.0%
) 2
 
2.0%
( 2
 
2.0%
1
 
1.0%
1 1
 
1.0%
2 1
 
1.0%
Hangul
ValueCountFrequency (%)
의 12
 
3.9%
계 11
 
3.6%
하 11
 
3.6%
는 9
 
2.9%
사 8
 
2.6%
가 7
 
2.3%
조 7
 
2.3%
통 7
 
2.3%
정 7
 
2.3%
제 6
 
2.0%
Other values (101) 222
72.3%

이미지설명글
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing79
Missing (%)80.6%
Memory size916.0 B
2023-12-12T16:01:49.279474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.3157895
Min length4

Characters and Unicode

Total characters139
Distinct characters59
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row인구주택총조사 메인 이미지
2nd row가계동향조사
3rd row가계금융조사
4th row사회조사
5th row생활시간조사
ValueCountFrequency (%)
인구주택총조사 2
 
9.1%
이미지 2
 
9.1%
녹색생활조사 1
 
4.5%
도소매업및서비스업조사 1
 
4.5%
경제총조사 1
 
4.5%
운수업조사 1
 
4.5%
건설업조사 1
 
4.5%
광업제조업조사 1
 
4.5%
영리법인기업체행정통계 1
 
4.5%
기업생멸행정통계 1
 
4.5%
Other values (10) 10
45.5%
2023-12-12T16:01:49.659298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 19
 
13.7%
조 17
 
12.2%
업 11
 
7.9%
인 4
 
2.9%
계 4
 
2.9%
기 4
 
2.9%
비 3
 
2.2%
스 3
 
2.2%
생 3
 
2.2%
활 3
 
2.2%
Other values (49) 68
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
97.8%
Space Separator 3
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 19
 
14.0%
조 17
 
12.5%
업 11
 
8.1%
인 4
 
2.9%
계 4
 
2.9%
기 4
 
2.9%
비 3
 
2.2%
스 3
 
2.2%
생 3
 
2.2%
활 3
 
2.2%
Other values (48) 65
47.8%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136
97.8%
Common 3
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 19
 
14.0%
조 17
 
12.5%
업 11
 
8.1%
인 4
 
2.9%
계 4
 
2.9%
기 4
 
2.9%
비 3
 
2.2%
스 3
 
2.2%
생 3
 
2.2%
활 3
 
2.2%
Other values (48) 65
47.8%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
97.8%
ASCII 3
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 19
 
14.0%
조 17
 
12.5%
업 11
 
8.1%
인 4
 
2.9%
계 4
 
2.9%
기 4
 
2.9%
비 3
 
2.2%
스 3
 
2.2%
생 3
 
2.2%
활 3
 
2.2%
Other values (48) 65
47.8%
ASCII
ValueCountFrequency (%)
3
100.0%

키워드1
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing96
Missing (%)98.0%
Memory size916.0 B
2023-12-12T16:01:49.834657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters11
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

Unique2 ?
Unique (%)100.0%

Sample

1st row인구주택총조사
2nd row농림어업총조사
ValueCountFrequency (%)
인구주택총조사 1
50.0%
농림어업총조사 1
50.0%
2023-12-12T16:01:50.177512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
총 2
14.3%
조 2
14.3%
사 2
14.3%
인 1
7.1%
구 1
7.1%
주 1
7.1%
택 1
7.1%
농 1
7.1%
림 1
7.1%
어 1
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
총 2
14.3%
조 2
14.3%
사 2
14.3%
인 1
7.1%
구 1
7.1%
주 1
7.1%
택 1
7.1%
농 1
7.1%
림 1
7.1%
어 1
7.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
총 2
14.3%
조 2
14.3%
사 2
14.3%
인 1
7.1%
구 1
7.1%
주 1
7.1%
택 1
7.1%
농 1
7.1%
림 1
7.1%
어 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
총 2
14.3%
조 2
14.3%
사 2
14.3%
인 1
7.1%
구 1
7.1%
주 1
7.1%
택 1
7.1%
농 1
7.1%
림 1
7.1%
어 1
7.1%

키워드2
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing96
Missing (%)98.0%
Memory size916.0 B
2023-12-12T16:01:50.333576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Characters and Unicode

Total characters7
Distinct characters7
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

Unique2 ?
Unique (%)100.0%

Sample

1st row인구총조사
2nd row농림
ValueCountFrequency (%)
인구총조사 1
50.0%
농림 1
50.0%
2023-12-12T16:01:50.627740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 1
14.3%
구 1
14.3%
총 1
14.3%
조 1
14.3%
사 1
14.3%
농 1
14.3%
림 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 1
14.3%
구 1
14.3%
총 1
14.3%
조 1
14.3%
사 1
14.3%
농 1
14.3%
림 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 1
14.3%
구 1
14.3%
총 1
14.3%
조 1
14.3%
사 1
14.3%
농 1
14.3%
림 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 1
14.3%
구 1
14.3%
총 1
14.3%
조 1
14.3%
사 1
14.3%
농 1
14.3%
림 1
14.3%

키워드3
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing96
Missing (%)98.0%
Memory size916.0 B
2023-12-12T16:01:50.780610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Characters and Unicode

Total characters5
Distinct characters5
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

Unique2 ?
Unique (%)100.0%

Sample

1st row총조사
2nd row어업
ValueCountFrequency (%)
총조사 1
50.0%
어업 1
50.0%
2023-12-12T16:01:51.064598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
총 1
20.0%
조 1
20.0%
사 1
20.0%
어 1
20.0%
업 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
총 1
20.0%
조 1
20.0%
사 1
20.0%
어 1
20.0%
업 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
총 1
20.0%
조 1
20.0%
사 1
20.0%
어 1
20.0%
업 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
총 1
20.0%
조 1
20.0%
사 1
20.0%
어 1
20.0%
업 1
20.0%

키워드4
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing96
Missing (%)98.0%
Memory size916.0 B
2023-12-12T16:01:51.201468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters6
Distinct characters6
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

Unique2 ?
Unique (%)100.0%

Sample

1st row인구
2nd row농림어업
ValueCountFrequency (%)
인구 1
50.0%
농림어업 1
50.0%
2023-12-12T16:01:51.505450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 1
16.7%
구 1
16.7%
농 1
16.7%
림 1
16.7%
어 1
16.7%
업 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 1
16.7%
구 1
16.7%
농 1
16.7%
림 1
16.7%
어 1
16.7%
업 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 1
16.7%
구 1
16.7%
농 1
16.7%
림 1
16.7%
어 1
16.7%
업 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 1
16.7%
구 1
16.7%
농 1
16.7%
림 1
16.7%
어 1
16.7%
업 1
16.7%

키워드5
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing96
Missing (%)98.0%
Memory size916.0 B
2023-12-12T16:01:51.642014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters5
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

Unique2 ?
Unique (%)100.0%

Sample

1st row인구총
2nd row총조사
ValueCountFrequency (%)
인구총 1
50.0%
총조사 1
50.0%
2023-12-12T16:01:52.200325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
총 2
33.3%
인 1
16.7%
구 1
16.7%
조 1
16.7%
사 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
총 2
33.3%
인 1
16.7%
구 1
16.7%
조 1
16.7%
사 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
총 2
33.3%
인 1
16.7%
구 1
16.7%
조 1
16.7%
사 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
총 2
33.3%
인 1
16.7%
구 1
16.7%
조 1
16.7%
사 1
16.7%

사전식보기초성ID
Categorical

Distinct12
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size916.0 B
W001
27 
W008
16 
W007
14 
W009
13 
W002
13 
Other values (7)
15 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st rowW009
2nd rowW008
3rd rowW008
4th rowW008
5th rowW001

Common Values

ValueCountFrequency (%)
W001 27
27.6%
W008 16
16.3%
W007 14
14.3%
W009 13
13.3%
W002 13
13.3%
W014 3
 
3.1%
W012 3
 
3.1%
W003 3
 
3.1%
W005 2
 
2.0%
W010 2
 
2.0%
Other values (2) 2
 
2.0%

Length

2023-12-12T16:01:52.319998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
w001 27
27.6%
w008 16
16.3%
w007 14
14.3%
w009 13
13.3%
w002 13
13.3%
w014 3
 
3.1%
w012 3
 
3.1%
w003 3
 
3.1%
w005 2
 
2.0%
w010 2
 
2.0%
Other values (2) 2
 
2.0%

Interactions

2023-12-12T16:01:46.532522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:01:52.413887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제목순번조사주기방식요약정보이미지설명글키워드1키워드2키워드3키워드4키워드5사전식보기초성ID
제목1.0000.9531.0001.0001.0001.0000.0000.0000.0000.0000.0001.000
순번0.9531.0000.4191.0001.0001.000NaNNaNNaNNaNNaN0.492
조사주기1.0000.4191.0000.0000.0001.000NaNNaNNaNNaNNaN0.223
방식1.0001.0000.0001.0001.0001.000NaNNaNNaNNaNNaN0.000
요약정보1.0001.0000.0001.0001.0000.0000.0000.0000.0000.0000.0001.000
이미지설명글1.0001.0001.0001.0000.0001.0000.0000.0000.0000.0000.0001.000
키워드10.000NaNNaNNaN0.0000.0001.0000.0000.0000.0000.0000.000
키워드20.000NaNNaNNaN0.0000.0000.0001.0000.0000.0000.0000.000
키워드30.000NaNNaNNaN0.0000.0000.0000.0001.0000.0000.0000.000
키워드40.000NaNNaNNaN0.0000.0000.0000.0000.0001.0000.0000.000
키워드50.000NaNNaNNaN0.0000.0000.0000.0000.0000.0001.0000.000
사전식보기초성ID1.0000.4920.2230.0001.0001.0000.0000.0000.0000.0000.0001.000
2023-12-12T16:01:52.550825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방식사전식보기초성ID조사주기
방식1.0000.0000.000
사전식보기초성ID0.0001.0000.051
조사주기0.0000.0511.000
2023-12-12T16:01:52.651815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번조사주기방식사전식보기초성ID
순번1.0000.2490.6320.226
조사주기0.2491.0000.0000.051
방식0.6320.0001.0000.000
사전식보기초성ID0.2260.0510.0001.000

Missing values

2023-12-12T16:01:46.664242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:01:46.850081image/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.
2023-12-12T16:01:47.023576image/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

제목순번조사주기방식요약정보이미지설명글키워드1키워드2키워드3키워드4키워드5사전식보기초성ID
0조사분류1<NA><NA><NA><NA><NA><NA><NA><NA><NA>W009
1인구·가구05년<NA><NA><NA><NA><NA><NA><NA><NA>W008
2인구총조사15년조사통계 > 전수조사우리나라의 모든 인구와 주택의 총수는 물론 개별 특성까지 파악하여 각종 경제 사회 발전계획의 수립 및 평가와 각종 학술연구, 민간부문의 경영계획수립에 활용하기 위해 실시하는 전국적 규모의 통계조사입니다. 이 조사는 지정통계 제1호(인구총조사)와 제2호(주택총조사)로 지정되어 있는 나라살림의 바탕이 되는 국가기본통계조사입니다.인구주택총조사 메인 이미지인구주택총조사인구총조사총조사인구인구총W008
3인구동향조사8월간<NA><NA><NA><NA><NA><NA><NA><NA>W008
4국내인구이동통계3<NA><NA><NA><NA><NA><NA><NA><NA><NA>W001
5국제인구이동통계4<NA><NA><NA><NA><NA><NA><NA><NA><NA>W001
6장래인구추계5<NA><NA><NA><NA><NA><NA><NA><NA><NA>W009
7장래가구추계6<NA><NA><NA><NA><NA><NA><NA><NA><NA>W009
8생명표7<NA><NA><NA><NA><NA><NA><NA><NA><NA>W007
9고용1<NA><NA><NA><NA><NA><NA><NA><NA><NA>W001
제목순번조사주기방식요약정보이미지설명글키워드1키워드2키워드3키워드4키워드5사전식보기초성ID
88기업특성별무역통계3연간<NA><NA><NA><NA><NA><NA><NA><NA>W001
89무역14<NA><NA><NA><NA><NA><NA><NA><NA><NA>W005
90퇴직연금통계5연간가공통계<NA><NA><NA><NA><NA><NA><NA>W012
91퇴직연금통계7연간<NA><NA><NA><NA><NA><NA><NA><NA>W012
92가계생산위성계정95년<NA><NA><NA><NA><NA><NA><NA><NA>W001
93임금근로일자리동향행정통계6분기<NA><NA><NA><NA><NA><NA><NA><NA>W008
94중장년층행정통계8연간<NA><NA><NA><NA><NA><NA><NA><NA>W009
95국민이전계정10연간<NA><NA><NA><NA><NA><NA><NA><NA>W001
96소상공인실태조사10연간<NA><NA><NA><NA><NA><NA><NA><NA>W007
97프렌차이즈조사10<NA><NA><NA><NA><NA><NA><NA><NA><NA>W013