Overview

Dataset statistics

Number of variables14
Number of observations36
Missing cells202
Missing cells (%)40.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory120.7 B

Variable types

Unsupported5
Text6
Categorical3

Dataset

Description개발촉진지구투자현황20163월말
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202675

Alerts

Unnamed: 6 is highly overall correlated with Unnamed: 9High correlation
Unnamed: 8 is highly overall correlated with Unnamed: 9High correlation
Unnamed: 9 is highly overall correlated with Unnamed: 6 and 1 other fieldsHigh correlation
Unnamed: 9 is highly imbalanced (77.0%)Imbalance
Unnamed: 0 has 36 (100.0%) missing valuesMissing
개발촉진지구(낙후지역 개발사업) 투자현황 및 계획 (단위:백만원) has 22 (61.1%) missing valuesMissing
Unnamed: 10 has 36 (100.0%) missing valuesMissing
Unnamed: 11 has 36 (100.0%) missing valuesMissing
Unnamed: 12 has 36 (100.0%) missing valuesMissing
Unnamed: 13 has 36 (100.0%) missing valuesMissing
Unnamed: 4 has unique valuesUnique
Unnamed: 0 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 started2024-03-14 01:29:23.777193
Analysis finished2024-03-14 01:29:24.492729
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

개발촉진지구(낙후지역 개발사업) 투자현황 및 계획 (단위:백만원)
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing22
Missing (%)61.1%
Memory size420.0 B
2024-03-14T10:29:24.597483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.7857143
Min length1

Characters and Unicode

Total characters39
Distinct characters33
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

Unique14 ?
Unique (%)100.0%

Sample

1st row시군
2nd row계
3rd row진안 임실
4th row장수
5th row순창
ValueCountFrequency (%)
시군 1
 
5.6%
계 1
 
5.6%
투자 1
 
5.6%
수요 1
 
5.6%
지역 1
 
5.6%
티브 1
 
5.6%
인센 1
 
5.6%
정읍 1
 
5.6%
부안 1
 
5.6%
김제 1
 
5.6%
Other values (8) 8
44.4%
2024-03-14T10:29:24.889169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
10.3%
수 2
 
5.1%
안 2
 
5.1%
창 2
 
5.1%
지 1
 
2.6%
읍 1
 
2.6%
인 1
 
2.6%
센 1
 
2.6%
티 1
 
2.6%
브 1
 
2.6%
Other values (23) 23
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35
89.7%
Control 4
 
10.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 2
 
5.7%
안 2
 
5.7%
창 2
 
5.7%
지 1
 
2.9%
읍 1
 
2.9%
인 1
 
2.9%
센 1
 
2.9%
티 1
 
2.9%
브 1
 
2.9%
시 1
 
2.9%
Other values (22) 22
62.9%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35
89.7%
Common 4
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 2
 
5.7%
안 2
 
5.7%
창 2
 
5.7%
지 1
 
2.9%
읍 1
 
2.9%
인 1
 
2.9%
센 1
 
2.9%
티 1
 
2.9%
브 1
 
2.9%
시 1
 
2.9%
Other values (22) 22
62.9%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35
89.7%
ASCII 4
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
수 2
 
5.7%
안 2
 
5.7%
창 2
 
5.7%
지 1
 
2.9%
읍 1
 
2.9%
인 1
 
2.9%
센 1
 
2.9%
티 1
 
2.9%
브 1
 
2.9%
시 1
 
2.9%
Other values (22) 22
62.9%

Unnamed: 2
Text

Distinct32
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T10:29:25.082724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length9.75
Min length1

Characters and Unicode

Total characters351
Distinct characters124
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

Unique31 ?
Unique (%)86.1%

Sample

1st row사 업 명
2nd row10개 시군
3rd row진안~관촌간도로
4th row장수관광순환도로 등
5th row모정~고원간도로 등
ValueCountFrequency (%)
계 5
 
6.7%
정비 4
 
5.3%
도로 3
 
4.0%
등 3
 
4.0%
조성사업 2
 
2.7%
탐방로 2
 
2.7%
연결도로 2
 
2.7%
임실 2
 
2.7%
기반시설 2
 
2.7%
명품경관정비사업 1
 
1.3%
Other values (49) 49
65.3%
2024-03-14T10:29:25.375741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
11.1%
로 19
 
5.4%
도 17
 
4.8%
지 11
 
3.1%
업 9
 
2.6%
관 9
 
2.6%
사 8
 
2.3%
산 7
 
2.0%
계 6
 
1.7%
마 6
 
1.7%
Other values (114) 220
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
86.9%
Space Separator 39
 
11.1%
Math Symbol 5
 
1.4%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 19
 
6.2%
도 17
 
5.6%
지 11
 
3.6%
업 9
 
3.0%
관 9
 
3.0%
사 8
 
2.6%
산 7
 
2.3%
계 6
 
2.0%
마 6
 
2.0%
비 6
 
2.0%
Other values (110) 207
67.9%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
86.9%
Common 46
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 19
 
6.2%
도 17
 
5.6%
지 11
 
3.6%
업 9
 
3.0%
관 9
 
3.0%
사 8
 
2.6%
산 7
 
2.3%
계 6
 
2.0%
마 6
 
2.0%
비 6
 
2.0%
Other values (110) 207
67.9%
Common
ValueCountFrequency (%)
39
84.8%
~ 5
 
10.9%
0 1
 
2.2%
1 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
86.9%
ASCII 46
 
13.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
84.8%
~ 5
 
10.9%
0 1
 
2.2%
1 1
 
2.2%
Hangul
ValueCountFrequency (%)
로 19
 
6.2%
도 17
 
5.6%
지 11
 
3.6%
업 9
 
3.0%
관 9
 
3.0%
사 8
 
2.6%
산 7
 
2.3%
계 6
 
2.0%
마 6
 
2.0%
비 6
 
2.0%
Other values (110) 207
67.9%

Unnamed: 3
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T10:29:25.564494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length12.611111
Min length4

Characters and Unicode

Total characters454
Distinct characters75
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)94.4%

Sample

1st row사업개요
2nd row38개 사업
3rd row1노선/13.1km B=10m
4th row3노선/21.9km
5th row3노선/22.2km
ValueCountFrequency (%)
1.4km/12m 2
 
3.4%
등 2
 
3.4%
5노선/18.4km 1
 
1.7%
7.7km/10m 1
 
1.7%
0.77km/15~25m 1
 
1.7%
1.9m/10m 1
 
1.7%
1.6km/18m 1
 
1.7%
2노선/3.35km 1
 
1.7%
관광시설 1
 
1.7%
4.74km/18.5~25m 1
 
1.7%
Other values (46) 46
79.3%
2024-03-14T10:29:25.874097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 50
 
11.0%
1 33
 
7.3%
. 32
 
7.0%
k 28
 
6.2%
/ 25
 
5.5%
2 24
 
5.3%
22
 
4.8%
5 21
 
4.6%
3 19
 
4.2%
4 14
 
3.1%
Other values (65) 186
41.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 157
34.6%
Other Letter 113
24.9%
Lowercase Letter 78
17.2%
Other Punctuation 70
15.4%
Space Separator 26
 
5.7%
Math Symbol 6
 
1.3%
Other Symbol 3
 
0.7%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
선 9
 
8.0%
노 9
 
8.0%
로 7
 
6.2%
장 4
 
3.5%
주 4
 
3.5%
차 4
 
3.5%
설 4
 
3.5%
개 4
 
3.5%
교 4
 
3.5%
등 3
 
2.7%
Other values (44) 61
54.0%
Decimal Number
ValueCountFrequency (%)
1 33
21.0%
2 24
15.3%
5 21
13.4%
3 19
12.1%
4 14
8.9%
0 12
 
7.6%
9 12
 
7.6%
7 11
 
7.0%
6 6
 
3.8%
8 5
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 32
45.7%
/ 25
35.7%
, 13
18.6%
Lowercase Letter
ValueCountFrequency (%)
m 50
64.1%
k 28
35.9%
Space Separator
ValueCountFrequency (%)
22
84.6%
　 4
 
15.4%
Math Symbol
ValueCountFrequency (%)
~ 5
83.3%
= 1
 
16.7%
Other Symbol
ValueCountFrequency (%)
㎡ 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 262
57.7%
Hangul 113
24.9%
Latin 79
 
17.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
선 9
 
8.0%
노 9
 
8.0%
로 7
 
6.2%
장 4
 
3.5%
주 4
 
3.5%
차 4
 
3.5%
설 4
 
3.5%
개 4
 
3.5%
교 4
 
3.5%
등 3
 
2.7%
Other values (44) 61
54.0%
Common
ValueCountFrequency (%)
1 33
12.6%
. 32
12.2%
/ 25
9.5%
2 24
9.2%
22
8.4%
5 21
8.0%
3 19
7.3%
4 14
 
5.3%
, 13
 
5.0%
0 12
 
4.6%
Other values (8) 47
17.9%
Latin
ValueCountFrequency (%)
m 50
63.3%
k 28
35.4%
B 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 334
73.6%
Hangul 113
 
24.9%
None 4
 
0.9%
CJK Compat 3
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 50
15.0%
1 33
9.9%
. 32
9.6%
k 28
8.4%
/ 25
 
7.5%
2 24
 
7.2%
22
 
6.6%
5 21
 
6.3%
3 19
 
5.7%
4 14
 
4.2%
Other values (9) 66
19.8%
Hangul
ValueCountFrequency (%)
선 9
 
8.0%
노 9
 
8.0%
로 7
 
6.2%
장 4
 
3.5%
주 4
 
3.5%
차 4
 
3.5%
설 4
 
3.5%
개 4
 
3.5%
교 4
 
3.5%
등 3
 
2.7%
Other values (44) 61
54.0%
None
ValueCountFrequency (%)
　 4
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 3
100.0%

Unnamed: 4
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T10:29:26.068239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5
Min length3

Characters and Unicode

Total characters198
Distinct characters16
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

Unique36 ?
Unique (%)100.0%

Sample

1st row총사업비
2nd row468,536
3rd row50,218
4th row61,600
5th row50,688
ValueCountFrequency (%)
총사업비 1
 
2.8%
468,536 1
 
2.8%
32,457 1
 
2.8%
13,000 1
 
2.8%
6,500 1
 
2.8%
4,700 1
 
2.8%
5,000 1
 
2.8%
11,000 1
 
2.8%
7,800 1
 
2.8%
4,145 1
 
2.8%
Other values (26) 26
72.2%
2024-03-14T10:29:26.450235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 47
23.7%
, 33
16.7%
1 21
10.6%
5 18
 
9.1%
7 17
 
8.6%
4 14
 
7.1%
6 14
 
7.1%
8 9
 
4.5%
2 9
 
4.5%
3 7
 
3.5%
Other values (6) 9
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
80.8%
Other Punctuation 33
 
16.7%
Other Letter 4
 
2.0%
Space Separator 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47
29.4%
1 21
13.1%
5 18
 
11.2%
7 17
 
10.6%
4 14
 
8.8%
6 14
 
8.8%
8 9
 
5.6%
2 9
 
5.6%
3 7
 
4.4%
9 4
 
2.5%
Other Letter
ValueCountFrequency (%)
총 1
25.0%
사 1
25.0%
업 1
25.0%
비 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 33
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 194
98.0%
Hangul 4
 
2.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 47
24.2%
, 33
17.0%
1 21
10.8%
5 18
 
9.3%
7 17
 
8.8%
4 14
 
7.2%
6 14
 
7.2%
8 9
 
4.6%
2 9
 
4.6%
3 7
 
3.6%
Other values (2) 5
 
2.6%
Hangul
ValueCountFrequency (%)
총 1
25.0%
사 1
25.0%
업 1
25.0%
비 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194
98.0%
Hangul 4
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 47
24.2%
, 33
17.0%
1 21
10.8%
5 18
 
9.3%
7 17
 
8.8%
4 14
 
7.2%
6 14
 
7.2%
8 9
 
4.6%
2 9
 
4.6%
3 7
 
3.6%
Other values (2) 5
 
2.6%
Hangul
ValueCountFrequency (%)
총 1
25.0%
사 1
25.0%
업 1
25.0%
비 1
25.0%

Unnamed: 5
Text

Distinct27
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T10:29:26.583168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.3055556
Min length1

Characters and Unicode

Total characters155
Distinct characters15
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

Unique26 ?
Unique (%)72.2%

Sample

1st row‘14까지
2nd row371,072
3rd row50,218
4th row61,600
5th row50,688
ValueCountFrequency (%)
0 10
27.8%
4,873 1
 
2.8%
2,176 1
 
2.8%
6,477 1
 
2.8%
2,200 1
 
2.8%
2,100 1
 
2.8%
3,367 1
 
2.8%
5,213 1
 
2.8%
21,533 1
 
2.8%
21,500 1
 
2.8%
Other values (17) 17
47.2%
2024-03-14T10:29:26.810515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 32
20.6%
, 25
16.1%
2 14
9.0%
7 13
8.4%
1 12
 
7.7%
3 11
 
7.1%
5 10
 
6.5%
8 10
 
6.5%
4 10
 
6.5%
6 9
 
5.8%
Other values (5) 9
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
81.3%
Other Punctuation 25
 
16.1%
Other Letter 2
 
1.3%
Initial Punctuation 1
 
0.6%
Space Separator 1
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32
25.4%
2 14
11.1%
7 13
10.3%
1 12
 
9.5%
3 11
 
8.7%
5 10
 
7.9%
8 10
 
7.9%
4 10
 
7.9%
6 9
 
7.1%
9 5
 
4.0%
Other Letter
ValueCountFrequency (%)
까 1
50.0%
지 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 153
98.7%
Hangul 2
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32
20.9%
, 25
16.3%
2 14
9.2%
7 13
8.5%
1 12
 
7.8%
3 11
 
7.2%
5 10
 
6.5%
8 10
 
6.5%
4 10
 
6.5%
6 9
 
5.9%
Other values (3) 7
 
4.6%
Hangul
ValueCountFrequency (%)
까 1
50.0%
지 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152
98.1%
Hangul 2
 
1.3%
Punctuation 1
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32
21.1%
, 25
16.4%
2 14
9.2%
7 13
8.6%
1 12
 
7.9%
3 11
 
7.2%
5 10
 
6.6%
8 10
 
6.6%
4 10
 
6.6%
6 9
 
5.9%
Other values (2) 6
 
3.9%
Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Hangul
ValueCountFrequency (%)
까 1
50.0%
지 1
50.0%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
19 
10,150
2 
5,401
 
1
4,147
 
1
1,565
 
1
Other values (12)
12 

Length

Max length6
Median length1
Mean length2.8888889
Min length1

Unique

Unique15 ?
Unique (%)41.7%

Sample

1st row‘15예산
2nd row31,575
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 19
52.8%
10,150 2
 
5.6%
5,401 1
 
2.8%
4,147 1
 
2.8%
1,565 1
 
2.8%
2,582 1
 
2.8%
6,101 1
 
2.8%
31,575 1
 
2.8%
700 1
 
2.8%
2,849 1
 
2.8%
Other values (7) 7
 
19.4%

Length

2024-03-14T10:29:26.926752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 19
52.8%
10,150 2
 
5.6%
2,849 1
 
2.8%
‘15예산 1
 
2.8%
10,927 1
 
2.8%
2,929 1
 
2.8%
1,300 1
 
2.8%
1,200 1
 
2.8%
2,649 1
 
2.8%
700 1
 
2.8%
Other values (7) 7
 
19.4%

Unnamed: 7
Text

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-03-14T10:29:27.041364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.8333333
Min length1

Characters and Unicode

Total characters102
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)52.8%

Sample

1st row‘16예산
2nd row13,417
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 13
36.1%
561 2
 
5.6%
1,538 2
 
5.6%
900 1
 
2.8%
‘16예산 1
 
2.8%
1,594 1
 
2.8%
297 1
 
2.8%
600 1
 
2.8%
100 1
 
2.8%
224 1
 
2.8%
Other values (12) 12
33.3%
2024-03-14T10:29:27.248846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30
29.4%
1 11
 
10.8%
5 10
 
9.8%
, 9
 
8.8%
2 9
 
8.8%
3 7
 
6.9%
6 7
 
6.9%
9 5
 
4.9%
4 5
 
4.9%
8 4
 
3.9%
Other values (4) 5
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
88.2%
Other Punctuation 9
 
8.8%
Other Letter 2
 
2.0%
Initial Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
33.3%
1 11
 
12.2%
5 10
 
11.1%
2 9
 
10.0%
3 7
 
7.8%
6 7
 
7.8%
9 5
 
5.6%
4 5
 
5.6%
8 4
 
4.4%
7 2
 
2.2%
Other Letter
ValueCountFrequency (%)
예 1
50.0%
산 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100
98.0%
Hangul 2
 
2.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30
30.0%
1 11
 
11.0%
5 10
 
10.0%
, 9
 
9.0%
2 9
 
9.0%
3 7
 
7.0%
6 7
 
7.0%
9 5
 
5.0%
4 5
 
5.0%
8 4
 
4.0%
Other values (2) 3
 
3.0%
Hangul
ValueCountFrequency (%)
예 1
50.0%
산 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99
97.1%
Hangul 2
 
2.0%
Punctuation 1
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30
30.3%
1 11
 
11.1%
5 10
 
10.1%
, 9
 
9.1%
2 9
 
9.1%
3 7
 
7.1%
6 7
 
7.1%
9 5
 
5.1%
4 5
 
5.1%
8 4
 
4.0%
Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Hangul
ValueCountFrequency (%)
예 1
50.0%
산 1
50.0%

Unnamed: 8
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
21 
‘17이후
 
1
52,472
 
1
9,158
 
1
2,658
 
1
Other values (11)
11 

Length

Max length6
Median length1
Mean length2.5833333
Min length1

Unique

Unique15 ?
Unique (%)41.7%

Sample

1st row‘17이후
2nd row52,472
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21
58.3%
‘17이후 1
 
2.8%
52,472 1
 
2.8%
9,158 1
 
2.8%
2,658 1
 
2.8%
439 1
 
2.8%
437 1
 
2.8%
5,624 1
 
2.8%
31,557 1
 
2.8%
3,645 1
 
2.8%
Other values (6) 6
 
16.7%

Length

2024-03-14T10:29:27.351595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 21
58.3%
‘17이후 1
 
2.8%
52,472 1
 
2.8%
9,158 1
 
2.8%
2,658 1
 
2.8%
439 1
 
2.8%
437 1
 
2.8%
5,624 1
 
2.8%
31,557 1
 
2.8%
3,645 1
 
2.8%
Other values (6) 6
 
16.7%

Unnamed: 9
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
?
34 
비고
 
1
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0555556
Min length2

Unique

Unique2 ?
Unique (%)5.6%

Sample

1st row비고
2nd row?
3rd row?
4th row?
5th row?

Common Values

ValueCountFrequency (%)
? 34
94.4%
비고 1
 
2.8%
<NA> 1
 
2.8%

Length

2024-03-14T10:29:27.464416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:29:27.561001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
34
94.4%
비고 1
 
2.8%
na 1
 
2.8%

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

Correlations

2024-03-14T10:29:27.623597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개발촉진지구(낙후지역 개발사업) 투자현황 및 계획 (단위:백만원)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
개발촉진지구(낙후지역 개발사업) 투자현황 및 계획 (단위:백만원)1.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0000.9741.0000.7990.0000.0000.8981.000
Unnamed: 31.0000.9741.0001.0000.9480.9500.9770.9371.000
Unnamed: 41.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0000.7990.9481.0001.0000.9890.0000.0001.000
Unnamed: 61.0000.0000.9501.0000.9891.0000.9810.0001.000
Unnamed: 71.0000.0000.9771.0000.0000.9811.0000.9611.000
Unnamed: 81.0000.8980.9371.0000.0000.0000.9611.0001.000
Unnamed: 91.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-14T10:29:27.723538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 9Unnamed: 6Unnamed: 8
Unnamed: 91.0000.7590.759
Unnamed: 60.7591.0000.000
Unnamed: 80.7590.0001.000
2024-03-14T10:29:27.794717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 6Unnamed: 8Unnamed: 9
Unnamed: 61.0000.0000.759
Unnamed: 80.0001.0000.759
Unnamed: 90.7590.7591.000

Missing values

2024-03-14T10:29:24.257751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:29:24.415086image/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

Unnamed: 0개발촉진지구(낙후지역 개발사업) 투자현황 및 계획 (단위:백만원)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
0<NA>시군사 업 명사업개요총사업비‘14까지‘15예산‘16예산‘17이후비고<NA><NA><NA><NA>
1<NA>계10개 시군38개 사업468,536371,07231,57513,41752,472?<NA><NA><NA><NA>
2<NA>진안 임실진안~관촌간도로1노선/13.1km B=10m50,21850,218000?<NA><NA><NA><NA>
3<NA>장수장수관광순환도로 등3노선/21.9km61,60061,600000?<NA><NA><NA><NA>
4<NA>순창모정~고원간도로 등3노선/22.2km50,68850,688000?<NA><NA><NA><NA>
5<NA>고창구시포~두어리간도로 등6노선/31.1km58,78758,787000?<NA><NA><NA><NA>
6<NA>무주계2노선/7.35km57,19752,4894,1475610?<NA><NA><NA><NA>
7<NA><NA>오산~당산간 도로3.79km/15m32,34130,2151,5655610?<NA><NA><NA><NA>
8<NA><NA>덕지~삼거간 도로3.56km/9~9.5m24,85622,2742,58200?<NA><NA><NA><NA>
9<NA>남원계5노선/18.4km46,56134,87310,1501,5380?<NA><NA><NA><NA>
Unnamed: 0개발촉진지구(낙후지역 개발사업) 투자현황 및 계획 (단위:백만원)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
26<NA>정읍계2노선/3.35km, 관광시설 등32,4570090031,557?<NA><NA><NA><NA>
27<NA><NA>구절초테마파크 기반시설 조성사업탐방로1.9km,출렁다리 97m, 주차장29,700㎡4,145005003,645?<NA><NA><NA><NA>
28<NA><NA>오감만족체험 축산테마파크 기반시설조성사업도로 0.41km, 진입교량 55m, 주차장5,620㎡2,770004002,370?<NA><NA><NA><NA>
29<NA><NA>영원 고분군마을 기반시설 조성사업탐방로개설4.3km, 주차장19,557㎡, 간위쉼터1식 등2,6050002,605?<NA><NA><NA><NA>
30<NA><NA>내장산리조트 연결도로 확장사업도로2.94km, 교량35m, 터널334m22,93700022,937?<NA><NA><NA><NA>
31<NA>인센 티브개발계획 미반영 사업김제 백석초등학교 진입로 개설47402502240?<NA><NA><NA><NA>
32<NA>지역 수요임실 오지마을 교통나눔 서비스수요응답형 대중교통100001000?<NA><NA><NA><NA>
33<NA><NA>임실 전통시장활성화사업다기능 주차장1,19700600597?<NA><NA><NA><NA>
34<NA><NA>고창 명품경관정비사업가로경관정비1,757002971,460?<NA><NA><NA><NA>
35<NA>투자 선도순창 한국전통 발효문화산업 투자선도지구진입도로, 내부기반시설10,000003009,700?<NA><NA><NA><NA>