Overview

Dataset statistics

Number of variables12
Number of observations161
Missing cells1137
Missing cells (%)58.9%
Duplicate rows12
Duplicate rows (%)7.5%
Total size in memory15.2 KiB
Average record size in memory96.8 B

Variable types

Unsupported4
Categorical1
Text7

Alerts

Unnamed: 7 has constant value ""Constant
Unnamed: 9 has constant value ""Constant
Unnamed: 10 has constant value ""Constant
Unnamed: 11 has constant value ""Constant
Dataset has 12 (7.5%) duplicate rowsDuplicates
Unnamed: 1 is highly imbalanced (65.2%)Imbalance
인공어초 설치현황(2011~2015) has 151 (93.8%) missing valuesMissing
Unnamed: 3 has 25 (15.5%) missing valuesMissing
Unnamed: 6 has 159 (98.8%) missing valuesMissing
Unnamed: 7 has 160 (99.4%) missing valuesMissing
Unnamed: 8 has 159 (98.8%) missing valuesMissing
Unnamed: 9 has 160 (99.4%) missing valuesMissing
Unnamed: 10 has 160 (99.4%) missing valuesMissing
Unnamed: 11 has 160 (99.4%) missing valuesMissing
인공어초 설치현황(2011~2015) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:37:37.503294
Analysis finished2024-03-14 00:37:38.110256
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

인공어초 설치현황(2011~2015)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)93.8%
Memory size1.4 KiB

Unnamed: 1
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
140 
군산시
15 
부안군
 
5
시군별
 
1

Length

Max length4
Median length4
Mean length3.8695652
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row시군별
2nd row<NA>
3rd row군산시
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 140
87.0%
군산시 15
 
9.3%
부안군 5
 
3.1%
시군별 1
 
0.6%

Length

2024-03-14T09:37:38.169191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:37:38.263362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 140
87.0%
군산시 15
 
9.3%
부안군 5
 
3.1%
시군별 1
 
0.6%

Unnamed: 2
Text

Distinct124
Distinct (%)77.5%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2024-03-14T09:37:38.512984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.11875
Min length1

Characters and Unicode

Total characters1139
Distinct characters72
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)70.0%

Sample

1st row투하수역
2nd row연도 C.24
3rd row연도 C.25
4th row소계
5th row어청도 E.35
ValueCountFrequency (%)
위도 40
 
14.3%
횡경도 22
 
7.9%
소계 20
 
7.2%
비안도 15
 
5.4%
연도 10
 
3.6%
관리도 10
 
3.6%
어청도 9
 
3.2%
서 8
 
2.9%
테트라형어초 4
 
1.4%
대형강제어초 4
 
1.4%
Other values (122) 137
49.1%
2024-03-14T09:37:38.878943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
10.4%
도 111
 
9.7%
. 111
 
9.7%
서 56
 
4.9%
B 48
 
4.2%
1 43
 
3.8%
3 41
 
3.6%
위 40
 
3.5%
어 31
 
2.7%
2 28
 
2.5%
Other values (62) 511
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 580
50.9%
Decimal Number 218
 
19.1%
Space Separator 119
 
10.4%
Other Punctuation 111
 
9.7%
Uppercase Letter 111
 
9.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 111
19.1%
서 56
 
9.7%
위 40
 
6.9%
어 31
 
5.3%
계 24
 
4.1%
초 22
 
3.8%
경 22
 
3.8%
횡 22
 
3.8%
소 20
 
3.4%
형 18
 
3.1%
Other values (44) 214
36.9%
Decimal Number
ValueCountFrequency (%)
1 43
19.7%
3 41
18.8%
2 28
12.8%
8 19
8.7%
4 18
8.3%
0 17
 
7.8%
9 17
 
7.8%
6 12
 
5.5%
7 12
 
5.5%
5 11
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 48
43.2%
C 26
23.4%
D 17
 
15.3%
A 10
 
9.0%
E 9
 
8.1%
F 1
 
0.9%
Space Separator
ValueCountFrequency (%)
119
100.0%
Other Punctuation
ValueCountFrequency (%)
. 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 580
50.9%
Common 448
39.3%
Latin 111
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 111
19.1%
서 56
 
9.7%
위 40
 
6.9%
어 31
 
5.3%
계 24
 
4.1%
초 22
 
3.8%
경 22
 
3.8%
횡 22
 
3.8%
소 20
 
3.4%
형 18
 
3.1%
Other values (44) 214
36.9%
Common
ValueCountFrequency (%)
119
26.6%
. 111
24.8%
1 43
 
9.6%
3 41
 
9.2%
2 28
 
6.2%
8 19
 
4.2%
4 18
 
4.0%
0 17
 
3.8%
9 17
 
3.8%
6 12
 
2.7%
Other values (2) 23
 
5.1%
Latin
ValueCountFrequency (%)
B 48
43.2%
C 26
23.4%
D 17
 
15.3%
A 10
 
9.0%
E 9
 
8.1%
F 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
50.9%
ASCII 559
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
21.3%
. 111
19.9%
B 48
8.6%
1 43
 
7.7%
3 41
 
7.3%
2 28
 
5.0%
C 26
 
4.7%
8 19
 
3.4%
4 18
 
3.2%
0 17
 
3.0%
Other values (8) 89
15.9%
Hangul
ValueCountFrequency (%)
도 111
19.1%
서 56
 
9.7%
위 40
 
6.9%
어 31
 
5.3%
계 24
 
4.1%
초 22
 
3.8%
경 22
 
3.8%
횡 22
 
3.8%
소 20
 
3.4%
형 18
 
3.1%
Other values (44) 214
36.9%

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing25
Missing (%)15.5%
Memory size1.4 KiB

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.6%
Memory size1.4 KiB

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.6%
Memory size1.4 KiB

Unnamed: 6
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing159
Missing (%)98.8%
Memory size1.4 KiB
2024-03-14T09:37:39.000283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9
Min length6

Characters and Unicode

Total characters18
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row설치좌표 (동경데이텀)
2nd row위 도
ValueCountFrequency (%)
설치좌표 1
25.0%
동경데이텀 1
25.0%
위 1
25.0%
도 1
25.0%
2024-03-14T09:37:39.209903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
27.8%
설 1
 
5.6%
치 1
 
5.6%
좌 1
 
5.6%
표 1
 
5.6%
( 1
 
5.6%
동 1
 
5.6%
경 1
 
5.6%
데 1
 
5.6%
이 1
 
5.6%
Other values (4) 4
22.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
61.1%
Space Separator 5
27.8%
Open Punctuation 1
 
5.6%
Close Punctuation 1
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 1
9.1%
치 1
9.1%
좌 1
9.1%
표 1
9.1%
동 1
9.1%
경 1
9.1%
데 1
9.1%
이 1
9.1%
텀 1
9.1%
위 1
9.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
61.1%
Common 7
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 1
9.1%
치 1
9.1%
좌 1
9.1%
표 1
9.1%
동 1
9.1%
경 1
9.1%
데 1
9.1%
이 1
9.1%
텀 1
9.1%
위 1
9.1%
Common
ValueCountFrequency (%)
5
71.4%
( 1
 
14.3%
) 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
61.1%
ASCII 7
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
71.4%
( 1
 
14.3%
) 1
 
14.3%
Hangul
ValueCountFrequency (%)
설 1
9.1%
치 1
9.1%
좌 1
9.1%
표 1
9.1%
동 1
9.1%
경 1
9.1%
데 1
9.1%
이 1
9.1%
텀 1
9.1%
위 1
9.1%

Unnamed: 7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing160
Missing (%)99.4%
Memory size1.4 KiB
2024-03-14T09:37:39.313439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters3
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

Unique1 ?
Unique (%)100.0%

Sample

1st row경 도
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%
2024-03-14T09:37:39.528214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
66.7%
경 1
 
16.7%
도 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Space Separator 4
66.7%
Other Letter 2
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
66.7%
Hangul 2
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
66.7%
Hangul 2
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing159
Missing (%)98.8%
Memory size1.4 KiB
2024-03-14T09:37:39.664038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9.5
Mean length9.5
Min length6

Characters and Unicode

Total characters19
Distinct characters14
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
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 row설치좌표 (WGS 84)
2nd row위 도
ValueCountFrequency (%)
설치좌표 1
20.0%
wgs 1
20.0%
84 1
20.0%
위 1
20.0%
도 1
20.0%
2024-03-14T09:37:39.900623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
31.6%
설 1
 
5.3%
치 1
 
5.3%
좌 1
 
5.3%
표 1
 
5.3%
( 1
 
5.3%
W 1
 
5.3%
G 1
 
5.3%
S 1
 
5.3%
8 1
 
5.3%
Other values (4) 4
21.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 6
31.6%
Other Letter 6
31.6%
Uppercase Letter 3
15.8%
Decimal Number 2
 
10.5%
Open Punctuation 1
 
5.3%
Close Punctuation 1
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 1
16.7%
치 1
16.7%
좌 1
16.7%
표 1
16.7%
위 1
16.7%
도 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
W 1
33.3%
G 1
33.3%
S 1
33.3%
Decimal Number
ValueCountFrequency (%)
8 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
52.6%
Hangul 6
31.6%
Latin 3
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 1
16.7%
치 1
16.7%
좌 1
16.7%
표 1
16.7%
위 1
16.7%
도 1
16.7%
Common
ValueCountFrequency (%)
6
60.0%
( 1
 
10.0%
8 1
 
10.0%
4 1
 
10.0%
) 1
 
10.0%
Latin
ValueCountFrequency (%)
W 1
33.3%
G 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
68.4%
Hangul 6
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
46.2%
( 1
 
7.7%
W 1
 
7.7%
G 1
 
7.7%
S 1
 
7.7%
8 1
 
7.7%
4 1
 
7.7%
) 1
 
7.7%
Hangul
ValueCountFrequency (%)
설 1
16.7%
치 1
16.7%
좌 1
16.7%
표 1
16.7%
위 1
16.7%
도 1
16.7%

Unnamed: 9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing160
Missing (%)99.4%
Memory size1.4 KiB
2024-03-14T09:37:40.005455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters3
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

Unique1 ?
Unique (%)100.0%

Sample

1st row경 도
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%
2024-03-14T09:37:40.199374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
66.7%
경 1
 
16.7%
도 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Space Separator 4
66.7%
Other Letter 2
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
66.7%
Hangul 2
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
66.7%
Hangul 2
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
경 1
50.0%
도 1
50.0%

Unnamed: 10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing160
Missing (%)99.4%
Memory size1.4 KiB
2024-03-14T09:37:40.303574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row사업비(천 원)
ValueCountFrequency (%)
사업비(천 1
50.0%
원 1
50.0%
2024-03-14T09:37:40.524147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1
12.5%
업 1
12.5%
비 1
12.5%
( 1
12.5%
천 1
12.5%
1
12.5%
원 1
12.5%
) 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
62.5%
Open Punctuation 1
 
12.5%
Space Separator 1
 
12.5%
Close Punctuation 1
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1
20.0%
업 1
20.0%
비 1
20.0%
천 1
20.0%
원 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
62.5%
Common 3
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1
20.0%
업 1
20.0%
비 1
20.0%
천 1
20.0%
원 1
20.0%
Common
ValueCountFrequency (%)
( 1
33.3%
1
33.3%
) 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
62.5%
ASCII 3
37.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1
20.0%
업 1
20.0%
비 1
20.0%
천 1
20.0%
원 1
20.0%
ASCII
ValueCountFrequency (%)
( 1
33.3%
1
33.3%
) 1
33.3%

Unnamed: 11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing160
Missing (%)99.4%
Memory size1.4 KiB
2024-03-14T09:37:40.635606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
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

Unique1 ?
Unique (%)100.0%

Sample

1st row투하일자
ValueCountFrequency (%)
투하일자 1
100.0%
2024-03-14T09:37:40.838988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
투 1
25.0%
하 1
25.0%
일 1
25.0%
자 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
투 1
25.0%
하 1
25.0%
일 1
25.0%
자 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
투 1
25.0%
하 1
25.0%
일 1
25.0%
자 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
투 1
25.0%
하 1
25.0%
일 1
25.0%
자 1
25.0%

Correlations

2024-03-14T09:37:40.918807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 6Unnamed: 8
Unnamed: 11.000NaNNaN
Unnamed: 6NaN1.0000.000
Unnamed: 8NaN0.0001.000

Missing values

2024-03-14T09:37:37.724868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:37:37.863112image/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.
2024-03-14T09:37:38.001506image/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

인공어초 설치현황(2011~2015)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0설치년도시군별투하수역어초종류수량\n(개)면적(ha)설치좌표 (동경데이텀)<NA>설치좌표 (WGS 84)<NA>사업비(천 원)투하일자
1NaN<NA><NA>NaNNaNNaN위 도경 도위 도경 도<NA><NA>
22011군산시연도 C.24테트라형어초10016<NA><NA><NA><NA><NA><NA>
3NaN<NA>연도 C.25테트라형어초10016<NA><NA><NA><NA><NA><NA>
4NaN<NA>소계220032<NA><NA><NA><NA><NA><NA>
5NaN군산시어청도 E.35팔각상자형어초116<NA><NA><NA><NA><NA><NA>
6NaN<NA>어청도 E.36팔각상자형어초116<NA><NA><NA><NA><NA><NA>
7NaN<NA>소계2232<NA><NA><NA><NA><NA><NA>
8NaN군산시명도 D.8대형강제어초116<NA><NA><NA><NA><NA><NA>
9NaN<NA>명도 D.9대형강제어초116<NA><NA><NA><NA><NA><NA>
인공어초 설치현황(2011~2015)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
151NaN<NA>위도 서C.43팔각반구형강제어초116<NA><NA><NA><NA><NA><NA>
152NaN<NA>위도 서C.44팔각반구형강제어초116<NA><NA><NA><NA><NA><NA>
153NaN<NA>소계88128<NA><NA><NA><NA><NA><NA>
154계<NA>대형강제어초348<NA><NA><NA><NA><NA><NA>
155NaN<NA>팔각삼단격실형강제어초NaN348<NA><NA><NA><NA><NA><NA>
156NaN<NA>부체꼴베란다사각어초NaN7548<NA><NA><NA><NA><NA><NA>
157NaN<NA>테트라형어초NaN30048<NA><NA><NA><NA><NA><NA>
158NaN<NA>유선형격판사각어초NaN6096<NA><NA><NA><NA><NA><NA>
159NaN<NA>팔각반구형강제어초NaN580<NA><NA><NA><NA><NA><NA>
160NaN<NA>계NaN446368<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

Unnamed: 1Unnamed: 2Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11# duplicates
4<NA>소계<NA><NA><NA><NA><NA><NA>20
0<NA>계<NA><NA><NA><NA><NA><NA>4
1<NA>대형강제어초<NA><NA><NA><NA><NA><NA>4
6<NA>테트라형어초<NA><NA><NA><NA><NA><NA>4
2<NA>부체꼴베란다강제어초<NA><NA><NA><NA><NA><NA>2
3<NA>부체꼴베란다사각어초<NA><NA><NA><NA><NA><NA>2
5<NA>유선형격판사각어초<NA><NA><NA><NA><NA><NA>2
7<NA>팔각반구대형<NA><NA><NA><NA><NA><NA>2
8<NA>팔각반구형강제어초<NA><NA><NA><NA><NA><NA>2
9<NA>팔각삼단격실형강제어초<NA><NA><NA><NA><NA><NA>2