Overview

Dataset statistics

Number of variables6
Number of observations275
Missing cells243
Missing cells (%)14.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory52.5 B

Variable types

Categorical1
Text2
Numeric3

Dataset

Description재정자립도[최종] 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=38INIZI60A4PX7TUKKDD22724672&infSeq=1

Alerts

자체수입금액(원) is highly overall correlated with 자치단체예산규모(원) and 1 other fieldsHigh correlation
자치단체예산규모(원) is highly overall correlated with 자체수입금액(원) and 1 other fieldsHigh correlation
재정자립비율(%) is highly overall correlated with 자체수입금액(원) and 1 other fieldsHigh correlation
시군명 has 243 (88.4%) missing valuesMissing
자체수입금액(원) has unique valuesUnique
자치단체예산규모(원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:03:08.818438
Analysis finished2023-12-10 22:03:10.081280
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2020
243 
2021
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2020 243
88.4%
2021 32
 
11.6%

Length

2023-12-11T07:03:10.162168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:03:10.249645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 243
88.4%
2021 32
 
11.6%

시군명
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing243
Missing (%)88.4%
Memory size2.3 KiB
2023-12-11T07:03:10.414987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.09375
Min length3

Characters and Unicode

Total characters99
Distinct characters41
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

Unique32 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row경기도
3rd row고양시
4th row과천시
5th row광명시
ValueCountFrequency (%)
경기도 1
 
3.1%
고양시 1
 
3.1%
화성시 1
 
3.1%
하남시 1
 
3.1%
포천시 1
 
3.1%
평택시 1
 
3.1%
파주시 1
 
3.1%
이천시 1
 
3.1%
의정부시 1
 
3.1%
의왕시 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T07:03:10.744330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

자치단체명
Text

Distinct243
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T07:03:11.095115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.8872727
Min length4

Characters and Unicode

Total characters1344
Distinct characters133
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

Unique211 ?
Unique (%)76.7%

Sample

1st row경기가평군
2nd row경기본청
3rd row경기고양시
4th row경기과천시
5th row경기광명시
ValueCountFrequency (%)
경기가평군 2
 
0.7%
경기평택시 2
 
0.7%
경기안성시 2
 
0.7%
경기여주시 2
 
0.7%
경기용인시 2
 
0.7%
경기연천군 2
 
0.7%
경기양평군 2
 
0.7%
경기의왕시 2
 
0.7%
경기하남시 2
 
0.7%
경기이천시 2
 
0.7%
Other values (233) 255
92.7%
2023-12-11T07:03:11.577009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

자체수입금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0475118 × 1011
Minimum4.0346027 × 1010
Maximum2.2727251 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T07:03:11.744099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.0346027 × 1010
5-th percentile7.3221332 × 1010
Q11.1603305 × 1011
median2.0363209 × 1011
Q33.870565 × 1011
95-th percentile1.9088236 × 1012
Maximum2.2727251 × 1013
Range2.2686905 × 1013
Interquartile range (IQR)2.7102345 × 1011

Descriptive statistics

Standard deviation1.9825775 × 1012
Coefficient of variation (CV)3.2783359
Kurtosis84.629389
Mean6.0475118 × 1011
Median Absolute Deviation (MAD)9.86438 × 1010
Skewness8.7373485
Sum1.6630657 × 1014
Variance3.9306136 × 1024
MonotonicityNot monotonic
2023-12-11T07:03:11.886172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165590549000 1
 
0.4%
99239161000 1
 
0.4%
400210645000 1
 
0.4%
128121493000 1
 
0.4%
76381974000 1
 
0.4%
198746644000 1
 
0.4%
95025777000 1
 
0.4%
1576407235000 1
 
0.4%
203632086000 1
 
0.4%
141222566000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
40346027000 1
0.4%
51699332000 1
0.4%
53820748000 1
0.4%
54030005000 1
0.4%
59069767000 1
0.4%
60243369000 1
0.4%
61022667000 1
0.4%
64721529000 1
0.4%
65497298000 1
0.4%
67222609000 1
0.4%
ValueCountFrequency (%)
22727250620000 1
0.4%
18360088389000 1
0.4%
12970552400000 1
0.4%
4847399165000 1
0.4%
4672063910000 1
0.4%
3426372818000 1
0.4%
3214850475000 1
0.4%
2450480287000 1
0.4%
2210662725000 1
0.4%
2204892790000 1
0.4%

자치단체예산규모(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6104034 × 1012
Minimum2.0507508 × 1011
Maximum3.3988274 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T07:03:12.032785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0507508 × 1011
5-th percentile3.9543663 × 1011
Q15.5194993 × 1011
median8.29 × 1011
Q31.2756868 × 1012
95-th percentile5.3487502 × 1012
Maximum3.3988274 × 1013
Range3.3783199 × 1013
Interquartile range (IQR)7.2373689 × 1011

Descriptive statistics

Standard deviation3.515424 × 1012
Coefficient of variation (CV)2.1829462
Kurtosis55.790683
Mean1.6104034 × 1012
Median Absolute Deviation (MAD)2.896859 × 1011
Skewness7.0015305
Sum4.4286095 × 1014
Variance1.2358206 × 1025
MonotonicityNot monotonic
2023-12-11T07:03:12.179641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
635733341000 1
 
0.4%
539314097000 1
 
0.4%
971586038000 1
 
0.4%
513668699000 1
 
0.4%
333726786000 1
 
0.4%
672526400000 1
 
0.4%
504059117000 1
 
0.4%
3348179289000 1
 
0.4%
717343870000 1
 
0.4%
719502880000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
205075078000 1
0.4%
228378127000 1
0.4%
253538534000 1
0.4%
257300000000 1
0.4%
300588454000 1
0.4%
329000000000 1
0.4%
333726786000 1
0.4%
355732793000 1
0.4%
361500000000 1
0.4%
363835000000 1
0.4%
ValueCountFrequency (%)
33988273898000 1
0.4%
31147949987000 1
0.4%
28440162409000 1
0.4%
11239005369000 1
0.4%
10177658472000 1
0.4%
9965900000000 1
0.4%
8745718280000 1
0.4%
8547201076000 1
0.4%
8036955797000 1
0.4%
7790559582000 1
0.4%

재정자립비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct259
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.034873
Minimum12.33
Maximum72.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T07:03:12.316430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.33
5-th percentile15.694
Q120.255
median24.92
Q333.7
95-th percentile50.945
Maximum72.97
Range60.64
Interquartile range (IQR)13.445

Descriptive statistics

Standard deviation10.869183
Coefficient of variation (CV)0.38770224
Kurtosis1.5235532
Mean28.034873
Median Absolute Deviation (MAD)5.47
Skewness1.2688749
Sum7709.59
Variance118.13914
MonotonicityNot monotonic
2023-12-11T07:03:12.440138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.71 2
 
0.7%
17.23 2
 
0.7%
19.09 2
 
0.7%
35.89 2
 
0.7%
28.38 2
 
0.7%
20.34 2
 
0.7%
27.46 2
 
0.7%
20.05 2
 
0.7%
20.3 2
 
0.7%
20.71 2
 
0.7%
Other values (249) 255
92.7%
ValueCountFrequency (%)
12.33 1
0.4%
12.4 1
0.4%
13.22 1
0.4%
13.53 1
0.4%
13.97 1
0.4%
14.0 1
0.4%
14.61 1
0.4%
14.73 1
0.4%
15.04 1
0.4%
15.09 1
0.4%
ValueCountFrequency (%)
72.97 1
0.4%
66.9 1
0.4%
60.97 1
0.4%
59.45 1
0.4%
57.59 1
0.4%
56.98 1
0.4%
55.34 1
0.4%
54.66 1
0.4%
54.49 1
0.4%
54.31 1
0.4%

Interactions

2023-12-11T07:03:09.596725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.073179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.318599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.678973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.151087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.405181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.772567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.241537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:03:09.498353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:03:12.538304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명자체수입금액(원)자치단체예산규모(원)재정자립비율(%)
회계연도1.000NaN0.1580.0000.564
시군명NaN1.0001.0001.0001.000
자체수입금액(원)0.1581.0001.0000.9760.718
자치단체예산규모(원)0.0001.0000.9761.0000.595
재정자립비율(%)0.5641.0000.7180.5951.000
2023-12-11T07:03:12.643814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자체수입금액(원)자치단체예산규모(원)재정자립비율(%)회계연도
자체수입금액(원)1.0000.9170.8010.113
자치단체예산규모(원)0.9171.0000.5290.000
재정자립비율(%)0.8010.5291.0000.429
회계연도0.1130.0000.4291.000

Missing values

2023-12-11T07:03:09.882492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:03:10.027762image/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

회계연도시군명자치단체명자체수입금액(원)자치단체예산규모(원)재정자립비율(%)
02021가평군경기가평군16559054900063573334100026.05
12021경기도경기본청183600883890003398827389800054.02
22021고양시경기고양시1116146288000285006298600039.16
32021과천시경기과천시33464372300050022875000066.9
42021광명시경기광명시39713447700095456470700041.6
52021광주시경기광주시485539489000135361162700035.87
62021구리시경기구리시29981516300076048505100039.42
72021군포시경기군포시28264931300082963249700034.07
82021김포시경기김포시632317780000165129886800038.29
92021남양주시경기남양주시710793866000217253031400032.72
회계연도시군명자치단체명자체수입금액(원)자치단체예산규모(원)재정자립비율(%)
2652020<NA>경기의정부시372044917000134211836500027.72
2662020<NA>경기시흥시634493069000150555867100042.14
2672020<NA>경기파주시600910083000167581673400035.86
2682020<NA>경기광명시34708396700092939111800037.35
2692020<NA>경기김포시547260555000144536743900037.86
2702020<NA>경기군포시28066702800079837988800035.15
2712020<NA>경기광주시441086076000124175705200035.52
2722020<NA>경기이천시523583833000108795409300048.13
2732020<NA>경기양주시26179674700093822698400027.9
2742020<NA>경기오산시23242194200070087613300033.16