Overview

Dataset statistics

Number of variables7
Number of observations275
Missing cells243
Missing cells (%)12.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory61.5 B

Variable types

Categorical1
Text2
Numeric4

Dataset

Description재정자주도[당초] 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=A4GMSRBLIVXF5M3ARUXB22732394&infSeq=1

Alerts

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

Reproduction

Analysis started2023-12-10 21:54:31.480598
Analysis finished2023-12-10 21:54:33.440809
Duration1.96 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
2022
243 
2023
32 

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 (%)
2022 243
88.4%
2023 32
 
11.6%

Length

2023-12-11T06:54:33.517963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:54:33.616229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 243
88.4%
2023 32
 
11.6%

시군명
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing243
Missing (%)88.4%
Memory size2.3 KiB
2023-12-11T06:54:33.781796image/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%
2023-12-11T06:54:34.104708image/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
2023-12-11T06:54:34.428166image/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%
2023-12-11T06:54:34.940840image/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%
Mean5.8194144 × 1011
Minimum2.2998234 × 1010
Maximum2.3441623 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:54:35.114858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2998234 × 1010
5-th percentile4.4605345 × 1010
Q17.924316 × 1010
median1.6840821 × 1011
Q33.3926782 × 1011
95-th percentile1.8552315 × 1012
Maximum2.3441623 × 1013
Range2.3418625 × 1013
Interquartile range (IQR)2.6002466 × 1011

Descriptive statistics

Standard deviation2.012181 × 1012
Coefficient of variation (CV)3.4577036
Kurtosis82.761398
Mean5.8194144 × 1011
Median Absolute Deviation (MAD)9.7317231 × 1010
Skewness8.5852767
Sum1.600339 × 1014
Variance4.0488724 × 1024
MonotonicityNot monotonic
2023-12-11T06:54:35.280961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95545046000 1
 
0.4%
146003467000 1
 
0.4%
192408022000 1
 
0.4%
165240804000 1
 
0.4%
82915781000 1
 
0.4%
69962632000 1
 
0.4%
2204388680000 1
 
0.4%
184639633000 1
 
0.4%
61060740000 1
 
0.4%
201703619000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
22998234000 1
0.4%
33391600000 1
0.4%
33689392000 1
0.4%
34681783000 1
0.4%
35839630000 1
0.4%
36144932000 1
0.4%
38519769000 1
0.4%
40617364000 1
0.4%
41194311000 1
0.4%
42001568000 1
0.4%
ValueCountFrequency (%)
23441622793000 1
0.4%
16171342231000 1
0.4%
15052705569000 1
0.4%
5204243140000 1
0.4%
4858263654000 1
0.4%
3592788740000 1
0.4%
3345123596000 1
0.4%
2706458301000 1
0.4%
2655710322000 1
0.4%
2654090584000 1
0.4%

자주재원금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8951721 × 1011
Minimum2.0460228 × 1010
Maximum1.749411 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:54:35.424066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0460228 × 1010
5-th percentile5.92608 × 1010
Q11.6417868 × 1011
median2.41863 × 1011
Q33.320605 × 1011
95-th percentile7.282248 × 1011
Maximum1.749411 × 1012
Range1.7289508 × 1012
Interquartile range (IQR)1.6788182 × 1011

Descriptive statistics

Standard deviation2.3929263 × 1011
Coefficient of variation (CV)0.826523
Kurtosis11.018015
Mean2.8951721 × 1011
Median Absolute Deviation (MAD)8.2233969 × 1010
Skewness2.8579524
Sum7.9617232 × 1013
Variance5.7260963 × 1022
MonotonicityNot monotonic
2023-12-11T06:54:35.562987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
216125583000 1
 
0.4%
124275000000 1
 
0.4%
52477000000 1
 
0.4%
101811000000 1
 
0.4%
102803000000 1
 
0.4%
110616000000 1
 
0.4%
1139000000000 1
 
0.4%
96197446000 1
 
0.4%
92607627000 1
 
0.4%
169581418000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
20460228000 1
0.4%
23602067000 1
0.4%
30261168000 1
0.4%
33500000000 1
0.4%
39431000000 1
0.4%
48700000000 1
0.4%
49324354000 1
0.4%
50058000000 1
0.4%
50686032000 1
0.4%
51997000000 1
0.4%
ValueCountFrequency (%)
1749411000000 1
0.4%
1579090000000 1
0.4%
1286900000000 1
0.4%
1208174000000 1
0.4%
1195456700000 1
0.4%
1153763000000 1
0.4%
1146220000000 1
0.4%
1139000000000 1
0.4%
1107650600000 1
0.4%
893500000000 1
0.4%

자치단체예산규모액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct274
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4747217 × 1012
Minimum1.6694544 × 1011
Maximum2.947474 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:54:35.723129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6694544 × 1011
5-th percentile3.5384416 × 1011
Q15.0052025 × 1011
median7.2 × 1011
Q31.0712129 × 1012
95-th percentile5.2679155 × 1012
Maximum2.947474 × 1013
Range2.9307794 × 1013
Interquartile range (IQR)5.7069266 × 1011

Descriptive statistics

Standard deviation3.239401 × 1012
Coefficient of variation (CV)2.1966184
Kurtosis51.402347
Mean1.4747217 × 1012
Median Absolute Deviation (MAD)2.521893 × 1011
Skewness6.7175174
Sum4.0554848 × 1014
Variance1.0493719 × 1025
MonotonicityNot monotonic
2023-12-11T06:54:35.875265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
720000000000 2
 
0.7%
943339236000 1
 
0.4%
651786349000 1
 
0.4%
869129000000 1
 
0.4%
561368755000 1
 
0.4%
619599876000 1
 
0.4%
5207512000000 1
 
0.4%
839573395000 1
 
0.4%
462298820000 1
 
0.4%
3524312284000 1
 
0.4%
Other values (264) 264
96.0%
ValueCountFrequency (%)
166945436000 1
0.4%
196476971000 1
0.4%
215500000000 1
0.4%
243024278000 1
0.4%
280435723000 1
0.4%
287000000000 1
0.4%
301251647000 1
0.4%
308000000000 1
0.4%
314807864000 1
0.4%
324724497000 1
0.4%
ValueCountFrequency (%)
29474739847000 1
0.4%
27867189088000 1
0.4%
27786517979000 1
0.4%
10742852851000 1
0.4%
9732097256000 1
0.4%
9477400000000 1
0.4%
8921142434000 1
0.4%
8844346252000 1
0.4%
7720100000000 1
0.4%
7532500000000 1
0.4%

재정자주비율(%)
Real number (ℝ)

Distinct259
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.699055
Minimum28.15
Maximum84.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:54:36.029289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28.15
5-th percentile34.672
Q155.225
median61.56
Q366.305
95-th percentile70.973
Maximum84.84
Range56.69
Interquartile range (IQR)11.08

Descriptive statistics

Standard deviation10.987354
Coefficient of variation (CV)0.1871811
Kurtosis0.47553676
Mean58.699055
Median Absolute Deviation (MAD)5.4
Skewness-1.0281555
Sum16142.24
Variance120.72195
MonotonicityNot monotonic
2023-12-11T06:54:36.175950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.97 2
 
0.7%
64.47 2
 
0.7%
66.25 2
 
0.7%
60.78 2
 
0.7%
63.85 2
 
0.7%
64.55 2
 
0.7%
62.33 2
 
0.7%
62.02 2
 
0.7%
62.27 2
 
0.7%
67.04 2
 
0.7%
Other values (249) 255
92.7%
ValueCountFrequency (%)
28.15 1
0.4%
28.65 1
0.4%
29.14 1
0.4%
30.23 1
0.4%
30.73 1
0.4%
31.96 1
0.4%
31.98 1
0.4%
32.45 1
0.4%
33.08 1
0.4%
33.45 1
0.4%
ValueCountFrequency (%)
84.84 1
0.4%
81.86 1
0.4%
80.23 1
0.4%
73.28 1
0.4%
72.37 1
0.4%
72.36 1
0.4%
71.76 1
0.4%
71.66 1
0.4%
71.47 1
0.4%
71.42 1
0.4%

Interactions

2023-12-11T06:54:32.800149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:31.752954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.070585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.413357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.915941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:31.824432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.146765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.509019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:33.051022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:31.918526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.241127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.611710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:33.151673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:31.996290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.328756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:54:32.700847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:54:36.290110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명자체수입금액(원)자주재원금액(원)자치단체예산규모액(원)재정자주비율(%)
회계연도1.000NaN0.0000.0000.0000.086
시군명NaN1.0001.0001.0001.0001.000
자체수입금액(원)0.0001.0001.0000.6960.9440.495
자주재원금액(원)0.0001.0000.6961.0000.7260.580
자치단체예산규모액(원)0.0001.0000.9440.7261.0000.394
재정자주비율(%)0.0861.0000.4950.5800.3941.000
2023-12-11T06:54:36.395283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자체수입금액(원)자주재원금액(원)자치단체예산규모액(원)재정자주비율(%)회계연도
자체수입금액(원)1.0000.2960.881-0.0790.000
자주재원금액(원)0.2961.0000.5760.2480.000
자치단체예산규모액(원)0.8810.5761.000-0.1130.000
재정자주비율(%)-0.0790.248-0.1131.0000.084
회계연도0.0000.0000.0000.0841.000

Missing values

2023-12-11T06:54:33.270352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:54:33.386536image/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)자주재원금액(원)자치단체예산규모액(원)재정자주비율(%)
02023가평군경기가평군9554504600021612558300046229882000067.42
12023경기도경기본청150527055690002065931820002778651797900054.92
22023고양시경기고양시965118507000560905000000256750041000059.44
32023과천시경기과천시20044217000010876200000037770283700081.86
42023광명시경기광명시37267286700022113100000088674441500066.96
52023광주시경기광주시429482886000231933000000109000233600060.68
62023구리시경기구리시21816250500016411100000059680155000064.05
72023군포시경기군포시25453032200018945000000072332097300061.38
82023김포시경기김포시582574888000278785260000140626593500061.25
92023남양주시경기남양주시619356047000487770000000190753543700058.04
회계연도시군명자치단체명자체수입금액(원)자주재원금액(원)자치단체예산규모액(원)재정자주비율(%)
2652022<NA>충남서산시310883547000351468000000101739944200065.1
2662022<NA>충남논산시12671894100041991100000084916854600064.37
2672022<NA>충남계룡시3339160000010636098000019647697100071.13
2682022<NA>충남당진시316383254000353549000000101093094900066.27
2692022<NA>충남금산군8589416800025278900000052303200000064.75
2702022<NA>충남부여군7387929400032164800000067650000000058.47
2712022<NA>충남서천군6066409300025139383300054491200000057.27
2722022<NA>충남청양군8089847200021819812800046028147400064.98
2732022<NA>충남홍성군14014834000027806274000067760000000061.72
2742022<NA>충남예산군8834050700031614938100067100538000060.28