Overview

Dataset statistics

Number of variables15
Number of observations24
Missing cells122
Missing cells (%)33.9%
Duplicate rows1
Duplicate rows (%)4.2%
Total size in memory2.9 KiB
Average record size in memory125.5 B

Variable types

Unsupported9
Text3
Categorical3

Dataset

Description공주시 주민자치센터 운영현황
Author충청남도 공주시
URLhttps://www.data.go.kr/data/3084525/fileData.do

Alerts

Dataset has 1 (4.2%) duplicate rowsDuplicates
Unnamed: 5 is highly overall correlated with Unnamed: 2 and 1 other fieldsHigh correlation
Unnamed: 2 is highly overall correlated with Unnamed: 5 and 1 other fieldsHigh correlation
Unnamed: 6 is highly overall correlated with Unnamed: 2 and 1 other fieldsHigh correlation
주민자치센터 설치 현황 (공주시) has 4 (16.7%) missing valuesMissing
Unnamed: 1 has 6 (25.0%) missing valuesMissing
Unnamed: 3 has 7 (29.2%) missing valuesMissing
Unnamed: 4 has 8 (33.3%) missing valuesMissing
Unnamed: 7 has 11 (45.8%) missing valuesMissing
Unnamed: 8 has 8 (33.3%) missing valuesMissing
Unnamed: 9 has 5 (20.8%) missing valuesMissing
Unnamed: 10 has 16 (66.7%) missing valuesMissing
Unnamed: 11 has 12 (50.0%) missing valuesMissing
Unnamed: 12 has 7 (29.2%) missing valuesMissing
Unnamed: 13 has 22 (91.7%) missing valuesMissing
Unnamed: 14 has 16 (66.7%) missing valuesMissing
주민자치센터 설치 현황 (공주시) 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: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 23:52:21.192071
Analysis finished2023-12-12 23:52:22.032930
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주민자치센터 설치 현황 (공주시)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)16.7%
Memory size324.0 B

Unnamed: 1
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing6
Missing (%)25.0%
Memory size324.0 B
2023-12-13T08:52:22.141916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length3
Mean length5.2222222
Min length3

Characters and Unicode

Total characters94
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row공주시
2nd row총16개( 읍1, 면9, 동6) // 설치완료14, 설치예정 1, 미설치 1)
3rd row유구읍
4th row이인면
5th row탄천면
ValueCountFrequency (%)
1 2
 
7.4%
공주시 1
 
3.7%
반포면 1
 
3.7%
신관동 1
 
3.7%
옥룡동 1
 
3.7%
금학동 1
 
3.7%
웅진동 1
 
3.7%
중학동 1
 
3.7%
신풍면 1
 
3.7%
사곡면 1
 
3.7%
Other values (16) 16
59.3%
2023-12-13T08:52:22.424985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 10
 
10.6%
9
 
9.6%
동 7
 
7.4%
1 5
 
5.3%
, 4
 
4.3%
설 3
 
3.2%
치 3
 
3.2%
신 2
 
2.1%
정 2
 
2.1%
학 2
 
2.1%
Other values (42) 47
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67
71.3%
Space Separator 9
 
9.6%
Decimal Number 9
 
9.6%
Other Punctuation 6
 
6.4%
Close Punctuation 2
 
2.1%
Open Punctuation 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 10
 
14.9%
동 7
 
10.4%
설 3
 
4.5%
치 3
 
4.5%
신 2
 
3.0%
정 2
 
3.0%
학 2
 
3.0%
룡 2
 
3.0%
읍 2
 
3.0%
진 1
 
1.5%
Other values (33) 33
49.3%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
6 2
 
22.2%
4 1
 
11.1%
9 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
/ 2
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67
71.3%
Common 27
28.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 10
 
14.9%
동 7
 
10.4%
설 3
 
4.5%
치 3
 
4.5%
신 2
 
3.0%
정 2
 
3.0%
학 2
 
3.0%
룡 2
 
3.0%
읍 2
 
3.0%
진 1
 
1.5%
Other values (33) 33
49.3%
Common
ValueCountFrequency (%)
9
33.3%
1 5
18.5%
, 4
14.8%
/ 2
 
7.4%
) 2
 
7.4%
6 2
 
7.4%
4 1
 
3.7%
( 1
 
3.7%
9 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67
71.3%
ASCII 27
28.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 10
 
14.9%
동 7
 
10.4%
설 3
 
4.5%
치 3
 
4.5%
신 2
 
3.0%
정 2
 
3.0%
학 2
 
3.0%
룡 2
 
3.0%
읍 2
 
3.0%
진 1
 
1.5%
Other values (33) 33
49.3%
ASCII
ValueCountFrequency (%)
9
33.3%
1 5
18.5%
, 4
14.8%
/ 2
 
7.4%
) 2
 
7.4%
6 2
 
7.4%
4 1
 
3.7%
( 1
 
3.7%
9 1
 
3.7%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
설치완료
14 
<NA>
7 
구분
 
1
설치예정
 
1
미설치
 
1

Length

Max length4
Median length4
Mean length3.875
Min length2

Unique

Unique3 ?
Unique (%)12.5%

Sample

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

Common Values

ValueCountFrequency (%)
설치완료 14
58.3%
<NA> 7
29.2%
구분 1
 
4.2%
설치예정 1
 
4.2%
미설치 1
 
4.2%

Length

2023-12-13T08:52:22.556140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:22.656747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설치완료 14
58.3%
na 7
29.2%
구분 1
 
4.2%
설치예정 1
 
4.2%
미설치 1
 
4.2%

Unnamed: 3
Text

MISSING 

Distinct12
Distinct (%)70.6%
Missing7
Missing (%)29.2%
Memory size324.0 B
2023-12-13T08:52:22.791962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.2941176
Min length4

Characters and Unicode

Total characters90
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)52.9%

Sample

1st row설치장소
2nd row(설치예정)
3rd row청사1,2층
4th row청사2층
5th row복지회관
ValueCountFrequency (%)
복지회관 4
21.1%
청사2,3층 2
10.5%
청사1,2,3층 2
10.5%
청사2층 2
10.5%
청사 2
10.5%
설치장소 1
 
5.3%
설치예정 1
 
5.3%
청사1,2층 1
 
5.3%
3층 1
 
5.3%
별도건물 1
 
5.3%
Other values (2) 2
10.5%
2023-12-13T08:52:23.375434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
층 9
 
10.0%
청 9
 
10.0%
사 9
 
10.0%
2 8
 
8.9%
, 7
 
7.8%
5
 
5.6%
3 5
 
5.6%
지 5
 
5.6%
복 4
 
4.4%
관 4
 
4.4%
Other values (16) 25
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60
66.7%
Decimal Number 16
 
17.8%
Other Punctuation 7
 
7.8%
Space Separator 5
 
5.6%
Close Punctuation 1
 
1.1%
Open Punctuation 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 9
15.0%
청 9
15.0%
사 9
15.0%
지 5
8.3%
복 4
 
6.7%
관 4
 
6.7%
회 4
 
6.7%
설 2
 
3.3%
치 2
 
3.3%
소 2
 
3.3%
Other values (9) 10
16.7%
Decimal Number
ValueCountFrequency (%)
2 8
50.0%
3 5
31.2%
1 3
 
18.8%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60
66.7%
Common 30
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 9
15.0%
청 9
15.0%
사 9
15.0%
지 5
8.3%
복 4
 
6.7%
관 4
 
6.7%
회 4
 
6.7%
설 2
 
3.3%
치 2
 
3.3%
소 2
 
3.3%
Other values (9) 10
16.7%
Common
ValueCountFrequency (%)
2 8
26.7%
, 7
23.3%
5
16.7%
3 5
16.7%
1 3
 
10.0%
) 1
 
3.3%
( 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60
66.7%
ASCII 30
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
층 9
15.0%
청 9
15.0%
사 9
15.0%
지 5
8.3%
복 4
 
6.7%
관 4
 
6.7%
회 4
 
6.7%
설 2
 
3.3%
치 2
 
3.3%
소 2
 
3.3%
Other values (9) 10
16.7%
ASCII
ValueCountFrequency (%)
2 8
26.7%
, 7
23.3%
5
16.7%
3 5
16.7%
1 3
 
10.0%
) 1
 
3.3%
( 1
 
3.3%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8
Missing (%)33.3%
Memory size324.0 B

Unnamed: 5
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
자체건물
13 
<NA>
7 
설치형태
 
1
(예정장소)
 
1
(자체건물)
 
1

Length

Max length6
Median length4
Mean length4.125
Min length3

Unique

Unique4 ?
Unique (%)16.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row설치형태
5th row(예정장소)

Common Values

ValueCountFrequency (%)
자체건물 13
54.2%
<NA> 7
29.2%
설치형태 1
 
4.2%
(예정장소) 1
 
4.2%
(자체건물) 1
 
4.2%
청사내 1
 
4.2%

Length

2023-12-13T08:52:23.520791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:23.617980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자체건물 14
58.3%
na 7
29.2%
설치형태 1
 
4.2%
예정장소 1
 
4.2%
청사내 1
 
4.2%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
주민자치센터
13 
<NA>
7 
공식 명칭
 
1
반포면 주민자치센터
 
1
자치센터
 
1

Length

Max length14
Median length6
Mean length5.7916667
Min length4

Unique

Unique4 ?
Unique (%)16.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row주민자치센터
5th row공식 명칭

Common Values

ValueCountFrequency (%)
주민자치센터 13
54.2%
<NA> 7
29.2%
공식 명칭 1
 
4.2%
반포면 주민자치센터 1
 
4.2%
자치센터 1
 
4.2%
공주시 사곡면 주민자치센터 1
 
4.2%

Length

2023-12-13T08:52:23.719664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:23.807929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주민자치센터 15
53.6%
na 7
25.0%
공식 1
 
3.6%
명칭 1
 
3.6%
반포면 1
 
3.6%
자치센터 1
 
3.6%
공주시 1
 
3.6%
사곡면 1
 
3.6%

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing11
Missing (%)45.8%
Memory size324.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8
Missing (%)33.3%
Memory size324.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5
Missing (%)20.8%
Memory size324.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing16
Missing (%)66.7%
Memory size324.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing12
Missing (%)50.0%
Memory size324.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)29.2%
Memory size324.0 B

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)91.7%
Memory size324.0 B

Unnamed: 14
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing16
Missing (%)66.7%
Memory size324.0 B
2023-12-13T08:52:23.943449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12.5
Mean length6.5
Min length2

Characters and Unicode

Total characters52
Distinct characters32
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

Unique4 ?
Unique (%)50.0%

Sample

1st row비고
2nd row설치계획,미설치사유등
3rd row2012년 청사신축시 이전
4th row복지회관 리모델링
5th row자체설치
ValueCountFrequency (%)
자체설치 4
36.4%
비고 1
 
9.1%
설치계획,미설치사유등 1
 
9.1%
2012년 1
 
9.1%
청사신축시 1
 
9.1%
이전 1
 
9.1%
복지회관 1
 
9.1%
리모델링 1
 
9.1%
2023-12-13T08:52:24.181535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
설 6
 
11.5%
치 6
 
11.5%
자 4
 
7.7%
체 4
 
7.7%
3
 
5.8%
2 2
 
3.8%
사 2
 
3.8%
복 1
 
1.9%
시 1
 
1.9%
이 1
 
1.9%
Other values (22) 22
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44
84.6%
Decimal Number 4
 
7.7%
Space Separator 3
 
5.8%
Other Punctuation 1
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 6
 
13.6%
치 6
 
13.6%
자 4
 
9.1%
체 4
 
9.1%
사 2
 
4.5%
복 1
 
2.3%
시 1
 
2.3%
이 1
 
2.3%
전 1
 
2.3%
지 1
 
2.3%
Other values (17) 17
38.6%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
0 1
25.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44
84.6%
Common 8
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 6
 
13.6%
치 6
 
13.6%
자 4
 
9.1%
체 4
 
9.1%
사 2
 
4.5%
복 1
 
2.3%
시 1
 
2.3%
이 1
 
2.3%
전 1
 
2.3%
지 1
 
2.3%
Other values (17) 17
38.6%
Common
ValueCountFrequency (%)
3
37.5%
2 2
25.0%
1 1
 
12.5%
0 1
 
12.5%
, 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44
84.6%
ASCII 8
 
15.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
설 6
 
13.6%
치 6
 
13.6%
자 4
 
9.1%
체 4
 
9.1%
사 2
 
4.5%
복 1
 
2.3%
시 1
 
2.3%
이 1
 
2.3%
전 1
 
2.3%
지 1
 
2.3%
Other values (17) 17
38.6%
ASCII
ValueCountFrequency (%)
3
37.5%
2 2
25.0%
1 1
 
12.5%
0 1
 
12.5%
, 1
 
12.5%

Correlations

2023-12-13T08:52:24.267604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 5Unnamed: 6Unnamed: 14
Unnamed: 11.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0000.0001.0000.6091.000
Unnamed: 31.0000.0001.0000.8310.8310.711
Unnamed: 51.0001.0000.8311.0000.9131.000
Unnamed: 61.0000.6090.8310.9131.0001.000
Unnamed: 141.0001.0000.7111.0001.0001.000
2023-12-13T08:52:24.361065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 5Unnamed: 2Unnamed: 6
Unnamed: 51.0000.9610.584
Unnamed: 20.9611.0000.594
Unnamed: 60.5840.5941.000
2023-12-13T08:52:24.455110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 5Unnamed: 6
Unnamed: 21.0000.9610.594
Unnamed: 50.9611.0000.584
Unnamed: 60.5940.5841.000

Missing values

2023-12-13T08:52:21.509863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:52:21.672746image/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.
2023-12-13T08:52:21.843280image/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

주민자치센터 설치 현황 (공주시)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
0NaN<NA><NA><NA>NaN<NA><NA>NaNNaNNaNNaNNaNNaNNaN<NA>
11. 주민자치센터 설치 현황 (미설치 읍면동 까지 포함 전수 조사 / 2014.1.1일 현재)<NA><NA><NA>NaN<NA><NA>NaNNaNNaNNaNNaNNaNNaN<NA>
2NaN<NA><NA><NA>NaN<NA><NA>NaNNaNNaNNaNNaNNaNNaN<NA>
3연번공주시구분설치장소연면적설치형태주민자치센터설치기간NaN설 치 예 산 (천원)NaNNaNNaNNaN비고
4NaN<NA><NA>(설치예정)(㎡)(예정장소)공식 명칭착공(예정)일준공(예정)일계국비도비시군비기타설치계획,미설치사유등
5계총16개( 읍1, 면9, 동6) // 설치완료14, 설치예정 1, 미설치 1)<NA><NA>NaN<NA><NA>NaNNaN1321706018522011364860<NA>
61유구읍설치완료청사1,2층393.4자체건물주민자치센터2003.11.262003.12.2352000NaNNaN52000NaN<NA>
72이인면설치완료청사2층332.2자체건물주민자치센터2007.3.5.2007.12.7.100000NaN4000060000NaN<NA>
83탄천면설치완료복지회관393자체건물주민자치센터2011.06.132011.8.2210000003000070000NaN<NA>
94계룡면설치완료복지회관608.5자체건물주민자치센터2003.02.17-33700NaNNaN33700NaN2012년 청사신축시 이전
주민자치센터 설치 현황 (공주시)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
149사곡면설치완료별도건물576.81자체건물공주시 사곡면 주민자치센터2011.05.132012.06.29253891NaN30041223850NaN<NA>
1510신풍면설치완료구보건지소259청사내주민자치센터2005.05.232005.10.20100000NaNNaN100000NaN<NA>
1611중학동설치완료청사 2층271.2자체건물주민자치센터NaN2003.02.2750014NaNNaN50014NaN<NA>
1712웅진동설치완료청사1,2,3층520자체건물주민자치센터NaN2003. 2. 25503000050300NaN자체설치
1813금학동설치완료청사2,3층215.5자체건물주민자치센터1991년2004년350000035000NaN자체설치
1914옥룡동설치완료청사2층330자체건물주민자치센터NaN2003.02.25.807060080706NaN자체설치
2015신관동설치완료청사1,2,3층354자체건물주민자치센터NaN2003.02.25555000055500NaN자체설치
2116월송동미설치<NA>NaN<NA><NA>NaNNaN0NaNNaNNaNNaN<NA>
22NaN<NA><NA><NA>NaN<NA><NA>NaNNaNNaNNaNNaNNaNNaN<NA>
23※ 미설치 읍면동 까지 전수조사 / 설치중(2013년도 이월사업), 설치예정(2014년도 신규사업)<NA><NA><NA>NaN<NA><NA>NaNNaNNaNNaNNaNNaNNaN<NA>

Duplicate rows

Most frequently occurring

Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 5Unnamed: 6Unnamed: 14# duplicates
0<NA><NA><NA><NA><NA><NA>5