Overview

Dataset statistics

Number of variables12
Number of observations3786
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory369.9 KiB
Average record size in memory100.0 B

Variable types

Categorical4
Text5
Numeric3

Dataset

Description경기도 성남시 성과지표별 실적현황에 대한 데이터로 년도, 관점, 지표유형, 전략목표, 성과목표, 성과지표, 지표산식, 목표값, 달성률, 비중 등의 항목을 제공합니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/15032496/fileData.do

Alerts

년도 has constant value ""Constant
비중 is highly overall correlated with 지표유형High correlation
관점 is highly overall correlated with 지표유형High correlation
지표유형 is highly overall correlated with 비중 and 1 other fieldsHigh correlation
단위 is highly imbalanced (66.6%)Imbalance
목표값 is highly skewed (γ1 = 40.33627818)Skewed
달성률 is highly skewed (γ1 = 52.50615983)Skewed
달성률 has 2214 (58.5%) zerosZeros
비중 has 68 (1.8%) zerosZeros

Reproduction

Analysis started2023-12-12 16:24:38.348882
Analysis finished2023-12-12 16:24:40.647710
Duration2.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
2023
3786 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 3786
100.0%

Length

2023-12-13T01:24:40.711554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:40.798083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 3786
100.0%

관점
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
자치행정
1357 
고객
1151 
학습과 성장
663 
재정
615 

Length

Max length6
Median length4
Mean length3.417327
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고객
2nd row고객
3rd row고객
4th row고객
5th row고객

Common Values

ValueCountFrequency (%)
자치행정 1357
35.8%
고객 1151
30.4%
학습과 성장 663
17.5%
재정 615
16.2%

Length

2023-12-13T01:24:40.913525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:41.047188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치행정 1357
30.5%
고객 1151
25.9%
학습과 663
14.9%
성장 663
14.9%
재정 615
13.8%

지표유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
고유
1909 
공통
1877 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공통
2nd row공통
3rd row공통
4th row공통
5th row공통

Common Values

ValueCountFrequency (%)
고유 1909
50.4%
공통 1877
49.6%

Length

2023-12-13T01:24:41.237241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:41.421220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고유 1909
50.4%
공통 1877
49.6%

전략목표
Text

Distinct86
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
2023-12-13T01:24:41.769304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length8.9302694
Min length6

Characters and Unicode

Total characters33810
Distinct characters141
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

Unique4 ?
Unique (%)0.1%

Sample

1st row시민만족도 제고
2nd row행정서비스 역량 강화
3rd row행정서비스 역량 강화
4th row행정서비스 역량 강화
5th row도시 이미지 제고
ValueCountFrequency (%)
강화 1288
 
14.5%
제고 693
 
7.8%
역량 536
 
6.0%
시민만족도 519
 
5.8%
행정서비스 508
 
5.7%
재정운영의 507
 
5.7%
합리화 507
 
5.7%
인재육성 495
 
5.6%
증진 286
 
3.2%
사회안정망 210
 
2.4%
Other values (118) 3342
37.6%
2023-12-13T01:24:42.284148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5105
 
15.1%
화 2075
 
6.1%
정 1592
 
4.7%
강 1379
 
4.1%
재 1094
 
3.2%
제 878
 
2.6%
도 871
 
2.6%
성 864
 
2.6%
리 843
 
2.5%
시 813
 
2.4%
Other values (131) 18296
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28705
84.9%
Space Separator 5105
 
15.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 2075
 
7.2%
정 1592
 
5.5%
강 1379
 
4.8%
재 1094
 
3.8%
제 878
 
3.1%
도 871
 
3.0%
성 864
 
3.0%
리 843
 
2.9%
시 813
 
2.8%
인 794
 
2.8%
Other values (130) 17502
61.0%
Space Separator
ValueCountFrequency (%)
5105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28705
84.9%
Common 5105
 
15.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 2075
 
7.2%
정 1592
 
5.5%
강 1379
 
4.8%
재 1094
 
3.8%
제 878
 
3.1%
도 871
 
3.0%
성 864
 
3.0%
리 843
 
2.9%
시 813
 
2.8%
인 794
 
2.8%
Other values (130) 17502
61.0%
Common
ValueCountFrequency (%)
5105
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28705
84.9%
ASCII 5105
 
15.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5105
100.0%
Hangul
ValueCountFrequency (%)
화 2075
 
7.2%
정 1592
 
5.5%
강 1379
 
4.8%
재 1094
 
3.8%
제 878
 
3.1%
도 871
 
3.0%
성 864
 
3.0%
리 843
 
2.9%
시 813
 
2.8%
인 794
 
2.8%
Other values (130) 17502
61.0%

성과목표
Text

Distinct183
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
2023-12-13T01:24:42.578943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length8.6286318
Min length5

Characters and Unicode

Total characters32668
Distinct characters200
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

Unique22 ?
Unique (%)0.6%

Sample

1st row행정서비스 향상
2nd row내부역량 강화
3rd row내부역량 강화
4th row내부역량 강화
5th row시정홍보 강화
ValueCountFrequency (%)
강화 1466
 
15.9%
운영 506
 
5.5%
효율적 488
 
5.3%
예산 488
 
5.3%
내부역량 485
 
5.3%
행정서비스 440
 
4.8%
향상 422
 
4.6%
역량 383
 
4.2%
내부인재 323
 
3.5%
확대 305
 
3.3%
Other values (241) 3910
42.4%
2023-12-13T01:24:43.019691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5430
 
16.6%
화 1999
 
6.1%
강 1616
 
4.9%
내 1041
 
3.2%
역 1039
 
3.2%
량 886
 
2.7%
부 811
 
2.5%
서 726
 
2.2%
비 716
 
2.2%
스 695
 
2.1%
Other values (190) 17709
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27238
83.4%
Space Separator 5430
 
16.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 1999
 
7.3%
강 1616
 
5.9%
내 1041
 
3.8%
역 1039
 
3.8%
량 886
 
3.3%
부 811
 
3.0%
서 726
 
2.7%
비 716
 
2.6%
스 695
 
2.6%
정 691
 
2.5%
Other values (189) 17018
62.5%
Space Separator
ValueCountFrequency (%)
5430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27238
83.4%
Common 5430
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 1999
 
7.3%
강 1616
 
5.9%
내 1041
 
3.8%
역 1039
 
3.8%
량 886
 
3.3%
부 811
 
3.0%
서 726
 
2.7%
비 716
 
2.6%
스 695
 
2.6%
정 691
 
2.5%
Other values (189) 17018
62.5%
Common
ValueCountFrequency (%)
5430
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27238
83.4%
ASCII 5430
 
16.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5430
100.0%
Hangul
ValueCountFrequency (%)
화 1999
 
7.3%
강 1616
 
5.9%
내 1041
 
3.8%
역 1039
 
3.8%
량 886
 
3.3%
부 811
 
3.0%
서 726
 
2.7%
비 716
 
2.6%
스 695
 
2.6%
정 691
 
2.5%
Other values (189) 17018
62.5%

성과지표
Text

Distinct995
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
2023-12-13T01:24:43.373267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length32
Mean length10.942684
Min length3

Characters and Unicode

Total characters41429
Distinct characters473
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

Unique699 ?
Unique (%)18.5%

Sample

1st row전화친절도
2nd row부서 협력도
3rd row부서 협력도
4th row정보보안활동 실적
5th row홍보실적
ValueCountFrequency (%)
실적 844
 
7.9%
적기 485
 
4.6%
집행률 484
 
4.6%
예산 482
 
4.5%
가정의 322
 
3.0%
양립 322
 
3.0%
일과 322
 
3.0%
부서 321
 
3.0%
협력도 321
 
3.0%
평가 185
 
1.7%
Other values (1686) 6547
61.6%
2023-12-13T01:24:43.874710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6849
 
16.5%
적 1843
 
4.4%
실 1342
 
3.2%
도 848
 
2.0%
율 818
 
2.0%
리 785
 
1.9%
정 738
 
1.8%
기 702
 
1.7%
률 699
 
1.7%
가 694
 
1.7%
Other values (463) 26111
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33918
81.9%
Space Separator 6849
 
16.5%
Other Punctuation 227
 
0.5%
Decimal Number 154
 
0.4%
Open Punctuation 103
 
0.2%
Close Punctuation 103
 
0.2%
Uppercase Letter 58
 
0.1%
Lowercase Letter 12
 
< 0.1%
Math Symbol 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
적 1843
 
5.4%
실 1342
 
4.0%
도 848
 
2.5%
율 818
 
2.4%
리 785
 
2.3%
정 738
 
2.2%
기 702
 
2.1%
률 699
 
2.1%
가 694
 
2.0%
보 659
 
1.9%
Other values (417) 24790
73.1%
Uppercase Letter
ValueCountFrequency (%)
E 7
12.1%
V 7
12.1%
S 7
12.1%
C 6
10.3%
T 5
8.6%
M 4
 
6.9%
P 3
 
5.2%
D 3
 
5.2%
A 3
 
5.2%
N 3
 
5.2%
Other values (6) 10
17.2%
Decimal Number
ValueCountFrequency (%)
2 38
24.7%
1 34
22.1%
8 22
14.3%
3 16
10.4%
0 16
10.4%
6 9
 
5.8%
5 8
 
5.2%
9 6
 
3.9%
4 3
 
1.9%
7 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
· 127
55.9%
, 32
 
14.1%
# 20
 
8.8%
& 20
 
8.8%
; 20
 
8.8%
. 4
 
1.8%
/ 4
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 99
96.1%
[ 3
 
2.9%
「 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 99
96.1%
] 3
 
2.9%
」 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
66.7%
r 2
 
16.7%
i 2
 
16.7%
Math Symbol
ValueCountFrequency (%)
~ 2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
6849
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33918
81.9%
Common 7441
 
18.0%
Latin 70
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
적 1843
 
5.4%
실 1342
 
4.0%
도 848
 
2.5%
율 818
 
2.4%
리 785
 
2.3%
정 738
 
2.2%
기 702
 
2.1%
률 699
 
2.1%
가 694
 
2.0%
보 659
 
1.9%
Other values (417) 24790
73.1%
Common
ValueCountFrequency (%)
6849
92.0%
· 127
 
1.7%
( 99
 
1.3%
) 99
 
1.3%
2 38
 
0.5%
1 34
 
0.5%
, 32
 
0.4%
8 22
 
0.3%
# 20
 
0.3%
& 20
 
0.3%
Other values (17) 101
 
1.4%
Latin
ValueCountFrequency (%)
e 8
11.4%
E 7
10.0%
V 7
10.0%
S 7
10.0%
C 6
 
8.6%
T 5
 
7.1%
M 4
 
5.7%
P 3
 
4.3%
D 3
 
4.3%
A 3
 
4.3%
Other values (9) 17
24.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33916
81.9%
ASCII 7382
 
17.8%
None 129
 
0.3%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6849
92.8%
( 99
 
1.3%
) 99
 
1.3%
2 38
 
0.5%
1 34
 
0.5%
, 32
 
0.4%
8 22
 
0.3%
# 20
 
0.3%
& 20
 
0.3%
; 20
 
0.3%
Other values (33) 149
 
2.0%
Hangul
ValueCountFrequency (%)
적 1843
 
5.4%
실 1342
 
4.0%
도 848
 
2.5%
율 818
 
2.4%
리 785
 
2.3%
정 738
 
2.2%
기 702
 
2.1%
률 699
 
2.1%
가 694
 
2.0%
보 659
 
1.9%
Other values (416) 24788
73.1%
None
ValueCountFrequency (%)
· 127
98.4%
「 1
 
0.8%
」 1
 
0.8%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

지표산식
Text

Distinct1103
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
2023-12-13T01:24:44.293018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length36
Mean length9.5699947
Min length3

Characters and Unicode

Total characters36232
Distinct characters431
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

Unique885 ?
Unique (%)23.4%

Sample

1st row전화친절도
2nd row부서별 상호만족도
3rd row전 직원 참여점수
4th row분기별 정보보안 활동실적
5th row보도자료 제출건수
ValueCountFrequency (%)
분기별 169
 
2.1%
준수율 169
 
2.1%
이수율 167
 
2.1%
직원 165
 
2.1%
활동실적 162
 
2.0%
참여점수 161
 
2.0%
전 161
 
2.0%
연가사용률 161
 
2.0%
정보보안 161
 
2.0%
소비투자집행실적 161
 
2.0%
Other values (1558) 6308
79.4%
2023-12-13T01:24:44.860680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4160
 
11.5%
율 1211
 
3.3%
수 1052
 
2.9%
적 922
 
2.5%
실 902
 
2.5%
도 715
 
2.0%
0 714
 
2.0%
률 649
 
1.8%
기 623
 
1.7%
행 618
 
1.7%
Other values (421) 24666
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29475
81.4%
Space Separator 4160
 
11.5%
Decimal Number 1173
 
3.2%
Open Punctuation 460
 
1.3%
Close Punctuation 460
 
1.3%
Other Punctuation 439
 
1.2%
Uppercase Letter 33
 
0.1%
Lowercase Letter 23
 
0.1%
Math Symbol 5
 
< 0.1%
Other Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
율 1211
 
4.1%
수 1052
 
3.6%
적 922
 
3.1%
실 902
 
3.1%
도 715
 
2.4%
률 649
 
2.2%
기 623
 
2.1%
행 618
 
2.1%
보 599
 
2.0%
가 599
 
2.0%
Other values (383) 21585
73.2%
Uppercase Letter
ValueCountFrequency (%)
C 6
18.2%
M 5
15.2%
E 5
15.2%
T 4
12.1%
V 4
12.1%
S 2
 
6.1%
D 2
 
6.1%
A 2
 
6.1%
B 1
 
3.0%
P 1
 
3.0%
Decimal Number
ValueCountFrequency (%)
0 714
60.9%
1 320
27.3%
5 53
 
4.5%
3 24
 
2.0%
7 18
 
1.5%
2 16
 
1.4%
8 10
 
0.9%
6 9
 
0.8%
4 8
 
0.7%
9 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
% 397
90.4%
· 12
 
2.7%
, 9
 
2.1%
# 5
 
1.1%
& 5
 
1.1%
; 5
 
1.1%
/ 4
 
0.9%
. 1
 
0.2%
* 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 4
80.0%
~ 1
 
20.0%
Other Number
ValueCountFrequency (%)
① 2
50.0%
② 2
50.0%
Space Separator
ValueCountFrequency (%)
4160
100.0%
Open Punctuation
ValueCountFrequency (%)
( 460
100.0%
Close Punctuation
ValueCountFrequency (%)
) 460
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29475
81.4%
Common 6701
 
18.5%
Latin 56
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
율 1211
 
4.1%
수 1052
 
3.6%
적 922
 
3.1%
실 902
 
3.1%
도 715
 
2.4%
률 649
 
2.2%
기 623
 
2.1%
행 618
 
2.1%
보 599
 
2.0%
가 599
 
2.0%
Other values (383) 21585
73.2%
Common
ValueCountFrequency (%)
4160
62.1%
0 714
 
10.7%
( 460
 
6.9%
) 460
 
6.9%
% 397
 
5.9%
1 320
 
4.8%
5 53
 
0.8%
3 24
 
0.4%
7 18
 
0.3%
2 16
 
0.2%
Other values (16) 79
 
1.2%
Latin
ValueCountFrequency (%)
e 23
41.1%
C 6
 
10.7%
M 5
 
8.9%
E 5
 
8.9%
T 4
 
7.1%
V 4
 
7.1%
S 2
 
3.6%
D 2
 
3.6%
A 2
 
3.6%
B 1
 
1.8%
Other values (2) 2
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29475
81.4%
ASCII 6741
 
18.6%
None 12
 
< 0.1%
Enclosed Alphanum 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4160
61.7%
0 714
 
10.6%
( 460
 
6.8%
) 460
 
6.8%
% 397
 
5.9%
1 320
 
4.7%
5 53
 
0.8%
3 24
 
0.4%
e 23
 
0.3%
7 18
 
0.3%
Other values (25) 112
 
1.7%
Hangul
ValueCountFrequency (%)
율 1211
 
4.1%
수 1052
 
3.6%
적 922
 
3.1%
실 902
 
3.1%
도 715
 
2.4%
률 649
 
2.2%
기 623
 
2.1%
행 618
 
2.1%
보 599
 
2.0%
가 599
 
2.0%
Other values (383) 21585
73.2%
None
ValueCountFrequency (%)
· 12
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 2
50.0%
② 2
50.0%

단위
Categorical

IMBALANCE 

Distinct39
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
%
2258 
점
974 
건
280 
점수
 
77
명
 
41
Other values (34)
 
156

Length

Max length6
Median length1
Mean length1.0578447
Min length1

Unique

Unique21 ?
Unique (%)0.6%

Sample

1st row점
2nd row점
3rd row점
4th row점
5th row건

Common Values

ValueCountFrequency (%)
% 2258
59.6%
점 974
25.7%
건 280
 
7.4%
점수 77
 
2.0%
명 41
 
1.1%
일 26
 
0.7%
세대 24
 
0.6%
건수 17
 
0.4%
세대수 16
 
0.4%
회 14
 
0.4%
Other values (29) 59
 
1.6%

Length

2023-12-13T01:24:45.053893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2265
59.7%
점 976
25.7%
건 280
 
7.4%
점수 77
 
2.0%
명 41
 
1.1%
일 26
 
0.7%
세대 25
 
0.7%
건수 17
 
0.4%
세대수 16
 
0.4%
회 14
 
0.4%
Other values (25) 55
 
1.5%

목표값
Real number (ℝ)

SKEWED 

Distinct522
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1657.128
Minimum0.13
Maximum1812000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.4 KiB
2023-12-13T01:24:45.189260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.13
5-th percentile2
Q18
median91.05
Q3100
95-th percentile100
Maximum1812000
Range1811999.9
Interquartile range (IQR)92

Descriptive statistics

Standard deviation35952.205
Coefficient of variation (CV)21.695491
Kurtosis1856.8601
Mean1657.128
Median Absolute Deviation (MAD)8.95
Skewness40.336278
Sum6273886.6
Variance1.292561 × 109
MonotonicityNot monotonic
2023-12-13T01:24:45.377176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 1069
28.2%
5.0 494
13.0%
95.0 343
 
9.1%
90.0 292
 
7.7%
2.0 180
 
4.8%
3.0 164
 
4.3%
93.0 66
 
1.7%
4.0 41
 
1.1%
80.0 33
 
0.9%
85.0 23
 
0.6%
Other values (512) 1081
28.6%
ValueCountFrequency (%)
0.13 1
 
< 0.1%
0.22 1
 
< 0.1%
0.87 1
 
< 0.1%
1.0 11
0.3%
1.1 1
 
< 0.1%
1.11 1
 
< 0.1%
1.3 1
 
< 0.1%
1.5 1
 
< 0.1%
1.6 1
 
< 0.1%
1.77 1
 
< 0.1%
ValueCountFrequency (%)
1812000.0 1
< 0.1%
976357.0 1
< 0.1%
494053.0 1
< 0.1%
434761.0 1
< 0.1%
223283.0 1
< 0.1%
163866.0 1
< 0.1%
139707.0 1
< 0.1%
132300.0 1
< 0.1%
124893.0 1
< 0.1%
122336.0 1
< 0.1%

달성률
Real number (ℝ)

SKEWED  ZEROS 

Distinct594
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean445.58325
Minimum0
Maximum732267
Zeros2214
Zeros (%)58.5%
Negative0
Negative (%)0.0%
Memory size33.4 KiB
2023-12-13T01:24:45.568105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q375
95-th percentile100
Maximum732267
Range732267
Interquartile range (IQR)75

Descriptive statistics

Standard deviation12608.483
Coefficient of variation (CV)28.296582
Kurtosis3006.8049
Mean445.58325
Median Absolute Deviation (MAD)0
Skewness52.50616
Sum1686978.2
Variance1.5897384 × 108
MonotonicityNot monotonic
2023-12-13T01:24:45.711639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2214
58.5%
100.0 300
 
7.9%
90.0 104
 
2.7%
95.0 97
 
2.6%
2.0 76
 
2.0%
60.0 64
 
1.7%
50.0 48
 
1.3%
70.0 23
 
0.6%
80.0 19
 
0.5%
75.0 13
 
0.3%
Other values (584) 828
 
21.9%
ValueCountFrequency (%)
0.0 2214
58.5%
1.0 11
 
0.3%
1.33 1
 
< 0.1%
1.42 1
 
< 0.1%
1.5 1
 
< 0.1%
1.54 1
 
< 0.1%
1.67 2
 
0.1%
1.73 1
 
< 0.1%
1.8 2
 
0.1%
1.87 1
 
< 0.1%
ValueCountFrequency (%)
732267.0 1
< 0.1%
122336.0 1
< 0.1%
104778.0 1
< 0.1%
99225.0 1
< 0.1%
93669.0 1
< 0.1%
89538.44 1
< 0.1%
81933.0 1
< 0.1%
46331.0 1
< 0.1%
41816.0 1
< 0.1%
28308.0 1
< 0.1%

비중
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2126255
Minimum0
Maximum40
Zeros68
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size33.4 KiB
2023-12-13T01:24:45.869517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median5
Q310
95-th percentile15
Maximum40
Range40
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.6912842
Coefficient of variation (CV)0.75512103
Kurtosis1.5263254
Mean6.2126255
Median Absolute Deviation (MAD)3
Skewness1.0549412
Sum23521
Variance22.008147
MonotonicityNot monotonic
2023-12-13T01:24:46.003363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
10.0 924
24.4%
3.0 841
22.2%
2.0 620
16.4%
1.0 264
 
7.0%
5.0 260
 
6.9%
15.0 169
 
4.5%
8.0 147
 
3.9%
4.0 97
 
2.6%
9.0 91
 
2.4%
0.0 68
 
1.8%
Other values (17) 305
 
8.1%
ValueCountFrequency (%)
0.0 68
 
1.8%
1.0 264
 
7.0%
2.0 620
16.4%
3.0 841
22.2%
4.0 97
 
2.6%
5.0 260
 
6.9%
6.0 33
 
0.9%
7.0 54
 
1.4%
7.5 4
 
0.1%
8.0 147
 
3.9%
ValueCountFrequency (%)
40.0 1
 
< 0.1%
30.0 3
 
0.1%
26.0 1
 
< 0.1%
25.0 11
 
0.3%
23.0 2
 
0.1%
22.0 3
 
0.1%
20.0 54
1.4%
18.0 2
 
0.1%
17.0 8
 
0.2%
16.0 6
 
0.2%

담당부서
Text

Distinct161
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size29.7 KiB
2023-12-13T01:24:46.533319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length15.816693
Min length12

Characters and Unicode

Total characters59882
Distinct characters153
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성남시>부시장실>공보관
2nd row성남시>부시장실>공보관
3rd row성남시>부시장실>공보관
4th row성남시>부시장실>공보관
5th row성남시>부시장실>공보관
ValueCountFrequency (%)
성남시>복지국>여성가족과 38
 
1.0%
성남시>행정기획조정실>정책기획과 33
 
0.9%
성남시>성남시중원구청>총무과 29
 
0.8%
성남시>부시장실>재난안전관 29
 
0.8%
성남시>푸른도시사업소>공원과 29
 
0.8%
성남시>환경보건국>위생정책과 29
 
0.8%
성남시>푸른도시사업소>녹지과 29
 
0.8%
성남시>교통도로국>도로과 28
 
0.7%
성남시>재정경제국>고용과 28
 
0.7%
성남시>교육문화체육국>미래교육과 28
 
0.7%
Other values (151) 3486
92.1%
2023-12-13T01:24:46.904014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
> 7572
 
12.6%
시 6379
 
10.7%
성 5882
 
9.8%
남 5820
 
9.7%
구 2257
 
3.8%
과 2233
 
3.7%
청 2057
 
3.4%
정 1844
 
3.1%
동 1262
 
2.1%
당 972
 
1.6%
Other values (143) 23604
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51402
85.8%
Math Symbol 7572
 
12.6%
Decimal Number 842
 
1.4%
Open Punctuation 33
 
0.1%
Close Punctuation 33
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 6379
 
12.4%
성 5882
 
11.4%
남 5820
 
11.3%
구 2257
 
4.4%
과 2233
 
4.3%
청 2057
 
4.0%
정 1844
 
3.6%
동 1262
 
2.5%
당 972
 
1.9%
분 972
 
1.9%
Other values (136) 21724
42.3%
Decimal Number
ValueCountFrequency (%)
1 312
37.1%
2 291
34.6%
3 145
17.2%
4 94
 
11.2%
Math Symbol
ValueCountFrequency (%)
> 7572
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51402
85.8%
Common 8480
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 6379
 
12.4%
성 5882
 
11.4%
남 5820
 
11.3%
구 2257
 
4.4%
과 2233
 
4.3%
청 2057
 
4.0%
정 1844
 
3.6%
동 1262
 
2.5%
당 972
 
1.9%
분 972
 
1.9%
Other values (136) 21724
42.3%
Common
ValueCountFrequency (%)
> 7572
89.3%
1 312
 
3.7%
2 291
 
3.4%
3 145
 
1.7%
4 94
 
1.1%
( 33
 
0.4%
) 33
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51402
85.8%
ASCII 8480
 
14.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
> 7572
89.3%
1 312
 
3.7%
2 291
 
3.4%
3 145
 
1.7%
4 94
 
1.1%
( 33
 
0.4%
) 33
 
0.4%
Hangul
ValueCountFrequency (%)
시 6379
 
12.4%
성 5882
 
11.4%
남 5820
 
11.3%
구 2257
 
4.4%
과 2233
 
4.3%
청 2057
 
4.0%
정 1844
 
3.6%
동 1262
 
2.5%
당 972
 
1.9%
분 972
 
1.9%
Other values (136) 21724
42.3%

Interactions

2023-12-13T01:24:40.106171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:39.487824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:39.814330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:40.192173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:39.591869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:39.919731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:40.284570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:39.694867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:24:40.010602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:24:47.001333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관점지표유형전략목표단위목표값달성률비중
관점1.0000.9361.0000.6700.0000.0000.592
지표유형0.9361.0000.9750.5080.0130.0220.918
전략목표1.0000.9751.0000.9120.4560.0000.823
단위0.6700.5080.9121.0000.6800.3710.446
목표값0.0000.0130.4560.6801.0000.7180.000
달성률0.0000.0220.0000.3710.7181.0000.076
비중0.5920.9180.8230.4460.0000.0761.000
2023-12-13T01:24:47.093110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지표유형단위관점
지표유형1.0000.4270.770
단위0.4271.0000.406
관점0.7700.4061.000
2023-12-13T01:24:47.170834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
목표값달성률비중관점지표유형단위
목표값1.0000.3840.2240.0000.0160.392
달성률0.3841.0000.0810.0000.0360.185
비중0.2240.0811.0000.4420.9920.164
관점0.0000.0000.4421.0000.7700.406
지표유형0.0160.0360.9920.7701.0000.427
단위0.3920.1850.1640.4060.4271.000

Missing values

2023-12-13T01:24:40.408246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:24:40.579149image/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

년도관점지표유형전략목표성과목표성과지표지표산식단위목표값달성률비중담당부서
02023고객공통시민만족도 제고행정서비스 향상전화친절도전화친절도점5.00.03.0성남시>부시장실>공보관
12023고객공통행정서비스 역량 강화내부역량 강화부서 협력도부서별 상호만족도점5.00.03.0성남시>부시장실>공보관
22023고객공통행정서비스 역량 강화내부역량 강화부서 협력도전 직원 참여점수점5.00.03.0성남시>부시장실>공보관
32023고객공통행정서비스 역량 강화내부역량 강화정보보안활동 실적분기별 정보보안 활동실적점3.00.03.0성남시>부시장실>공보관
42023고객공통도시 이미지 제고시정홍보 강화홍보실적보도자료 제출건수건53.025.01.0성남시>부시장실>공보관
52023고객고유도시 이미지 제고시민홍보 강화관내 매체 홍보 콘텐츠 수관내 매체 홍보 콘텐츠 수건35.027.07.0성남시>부시장실>공보관
62023고객고유도시 이미지 제고시민홍보 강화비전성남 독자 확보 실적콘텐츠 제작 건수건98.69118.1110.0성남시>부시장실>공보관
72023고객고유도시 이미지 제고시민홍보 강화비전성남 독자 확보 실적홈페이지 접속 건수건104488.089538.4410.0성남시>부시장실>공보관
82023고객고유도시 이미지 제고시민홍보 강화시정홍보 만족도시정홍보 만족도 결과점63.50.08.0성남시>부시장실>공보관
92023고객고유도시 이미지 제고시민홍보 강화SNS를 통한 시정홍보 실적페이스북 시정홍보 게시물 도달범위명8795.027734.4510.0성남시>부시장실>공보관
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