Overview

Dataset statistics

Number of variables10
Number of observations275
Missing cells243
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.5 KiB
Average record size in memory87.5 B

Variable types

Categorical2
Text2
Numeric6

Dataset

Description중기지방재정계획 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=S6JFJ96ZQRVAD6VGSWRF22802883&infSeq=1

Alerts

세입세출구분명 has constant value ""Constant
1차년도금액(원) is highly overall correlated with 2차년도금액(원) and 3 other fieldsHigh correlation
2차년도금액(원) is highly overall correlated with 1차년도금액(원) and 3 other fieldsHigh correlation
3차년도금액(원) is highly overall correlated with 1차년도금액(원) and 3 other fieldsHigh correlation
4차년도금액(원) is highly overall correlated with 1차년도금액(원) and 3 other fieldsHigh correlation
5차년도금액(원) is highly overall correlated with 1차년도금액(원) and 3 other fieldsHigh correlation
시군명 has 243 (88.4%) missing valuesMissing
1차년도금액(원) has unique valuesUnique
2차년도금액(원) has unique valuesUnique
3차년도금액(원) has unique valuesUnique
4차년도금액(원) has unique valuesUnique
5차년도금액(원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:06:40.326281
Analysis finished2023-12-10 23:06:43.698312
Duration3.37 seconds
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

2023-12-11T08:06:43.768846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:06:43.895856image/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
2023-12-11T08:06:44.053069image/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%
2023-12-11T08:06:44.377061image/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
2023-12-11T08:06:44.695764image/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%
2023-12-11T08:06:45.189148image/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%

세입세출구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
세입합계
275 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세입합계 275
100.0%

Length

2023-12-11T08:06:45.357209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:06:45.441366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세입합계 275
100.0%

1차년도금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.093767 × 1012
Minimum2.4563756 × 1011
Maximum4.7467275 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:06:45.604242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.4563756 × 1011
5-th percentile4.2926916 × 1011
Q16.5139518 × 1011
median9.3851394 × 1011
Q31.6004503 × 1012
95-th percentile7.5265157 × 1012
Maximum4.7467275 × 1013
Range4.7221637 × 1013
Interquartile range (IQR)9.4905515 × 1011

Descriptive statistics

Standard deviation4.8419547 × 1012
Coefficient of variation (CV)2.3125566
Kurtosis54.907623
Mean2.093767 × 1012
Median Absolute Deviation (MAD)3.4513087 × 1011
Skewness6.9269384
Sum5.7578593 × 1014
Variance2.3444525 × 1025
MonotonicityNot monotonic
2023-12-11T08:06:45.731624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
852314508000 1
 
0.4%
1187227816000 1
 
0.4%
437829371000 1
 
0.4%
382708335000 1
 
0.4%
409841761000 1
 
0.4%
259812461000 1
 
0.4%
15927973532000 1
 
0.4%
944354179000 1
 
0.4%
1719711385000 1
 
0.4%
1071573200000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
245637560000 1
0.4%
259812461000 1
0.4%
316927000000 1
0.4%
351116154000 1
0.4%
373738307000 1
0.4%
378000000000 1
0.4%
382708335000 1
0.4%
397312487000 1
0.4%
405996973000 1
0.4%
409841761000 1
0.4%
ValueCountFrequency (%)
47467274682000 1
0.4%
40272841076000 1
0.4%
39938730652000 1
0.4%
15927973532000 1
0.4%
15028260583000 1
0.4%
13020516651000 1
0.4%
12763639824000 1
0.4%
11751163766000 1
0.4%
11636785459000 1
0.4%
9970419308000 1
0.4%

2차년도금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1549282 × 1012
Minimum2.4643416 × 1011
Maximum4.8297186 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:06:45.875010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.4643416 × 1011
5-th percentile4.3073781 × 1011
Q16.6486381 × 1011
median9.4231197 × 1011
Q31.6424942 × 1012
95-th percentile7.9447445 × 1012
Maximum4.8297186 × 1013
Range4.8050752 × 1013
Interquartile range (IQR)9.7763041 × 1011

Descriptive statistics

Standard deviation4.9810809 × 1012
Coefficient of variation (CV)2.3114834
Kurtosis54.08275
Mean2.1549282 × 1012
Median Absolute Deviation (MAD)3.5364277 × 1011
Skewness6.871728
Sum5.9260526 × 1014
Variance2.4811167 × 1025
MonotonicityNot monotonic
2023-12-11T08:06:46.012144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
833207141000 1
 
0.4%
1203954961000 1
 
0.4%
441950686000 1
 
0.4%
386298909000 1
 
0.4%
412516491000 1
 
0.4%
266805227000 1
 
0.4%
16087894589000 1
 
0.4%
1115962962000 1
 
0.4%
1795209885000 1
 
0.4%
998165707000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
246434155000 1
0.4%
266805227000 1
0.4%
296567473000 1
0.4%
328183000000 1
0.4%
380241111000 1
0.4%
386298909000 1
0.4%
388000000000 1
0.4%
412516491000 1
0.4%
416096862000 1
0.4%
416184434000 1
0.4%
ValueCountFrequency (%)
48297186135000 1
0.4%
42080676609000 1
0.4%
40717500522000 1
0.4%
16087894589000 1
0.4%
15888941679000 1
0.4%
13368568067000 1
0.4%
13184155571000 1
0.4%
12100129039000 1
0.4%
12083973208000 1
0.4%
10374199206000 1
0.4%

3차년도금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2005083 × 1012
Minimum2.482591 × 1011
Maximum5.0494 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:06:46.145546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.482591 × 1011
5-th percentile4.3910058 × 1011
Q16.697176 × 1011
median9.621047 × 1011
Q31.6509257 × 1012
95-th percentile8.315974 × 1012
Maximum5.0494 × 1013
Range5.0245741 × 1013
Interquartile range (IQR)9.8120812 × 1011

Descriptive statistics

Standard deviation5.2173498 × 1012
Coefficient of variation (CV)2.3709748
Kurtosis55.321615
Mean2.2005083 × 1012
Median Absolute Deviation (MAD)3.6511255 × 1011
Skewness6.9741122
Sum6.0513978 × 1014
Variance2.7220739 × 1025
MonotonicityNot monotonic
2023-12-11T08:06:46.284073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
819981222000 1
 
0.4%
1246356684000 1
 
0.4%
454163550000 1
 
0.4%
401521416000 1
 
0.4%
418536852000 1
 
0.4%
276635318000 1
 
0.4%
16567399634000 1
 
0.4%
1036283317000 1
 
0.4%
1909306776000 1
 
0.4%
981756356000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
248259102000 1
0.4%
276635318000 1
0.4%
282737261000 1
0.4%
336316000000 1
0.4%
390258841000 1
0.4%
394000000000 1
0.4%
401521416000 1
0.4%
418536852000 1
0.4%
419223023000 1
0.4%
424910124000 1
0.4%
ValueCountFrequency (%)
50493999988000 1
0.4%
44223059694000 1
0.4%
43392483276000 1
0.4%
16567399634000 1
0.4%
16164662961000 1
0.4%
13456085896000 1
0.4%
13440992565000 1
0.4%
12650119751000 1
0.4%
12363544103000 1
0.4%
10557360546000 1
0.4%

4차년도금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2613596 × 1012
Minimum2.4981052 × 1011
Maximum5.3028307 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:06:46.426011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.4981052 × 1011
5-th percentile4.4860312 × 1011
Q16.8126196 × 1011
median9.7401578 × 1011
Q31.6389778 × 1012
95-th percentile8.5246669 × 1012
Maximum5.3028307 × 1013
Range5.2778496 × 1013
Interquartile range (IQR)9.5771582 × 1011

Descriptive statistics

Standard deviation5.4909489 × 1012
Coefficient of variation (CV)2.4281626
Kurtosis56.648949
Mean2.2613596 × 1012
Median Absolute Deviation (MAD)3.5892894 × 1011
Skewness7.0778464
Sum6.2187389 × 1014
Variance3.0150519 × 1025
MonotonicityNot monotonic
2023-12-11T08:06:46.832973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
809825486000 1
 
0.4%
1240395620000 1
 
0.4%
464080907000 1
 
0.4%
421007472000 1
 
0.4%
423912745000 1
 
0.4%
293056642000 1
 
0.4%
16919303086000 1
 
0.4%
1010552806000 1
 
0.4%
1972447795000 1
 
0.4%
967988771000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
249810523000 1
0.4%
289082109000 1
0.4%
293056642000 1
0.4%
346543000000 1
0.4%
398740791000 1
0.4%
403000000000 1
0.4%
421007472000 1
0.4%
421894568000 1
0.4%
423538336000 1
0.4%
423912745000 1
0.4%
ValueCountFrequency (%)
53028306900000 1
0.4%
47245869659000 1
0.4%
45934057866000 1
0.4%
16919303086000 1
0.4%
16452149002000 1
0.4%
13799997086000 1
0.4%
13770869753000 1
0.4%
13206180536000 1
0.4%
12621327615000 1
0.4%
10809265160000 1
0.4%

5차년도금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3262653 × 1012
Minimum2.516405 × 1011
Maximum5.4791396 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:06:46.994620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.516405 × 1011
5-th percentile4.5840165 × 1011
Q16.9763417 × 1011
median1.0082064 × 1012
Q31.6949057 × 1012
95-th percentile8.777558 × 1012
Maximum5.4791396 × 1013
Range5.4539756 × 1013
Interquartile range (IQR)9.972715 × 1011

Descriptive statistics

Standard deviation5.7245609 × 1012
Coefficient of variation (CV)2.4608375
Kurtosis57.293929
Mean2.3262653 × 1012
Median Absolute Deviation (MAD)3.7836575 × 1011
Skewness7.131035
Sum6.3972295 × 1014
Variance3.2770597 × 1025
MonotonicityNot monotonic
2023-12-11T08:06:47.146168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
842048315000 1
 
0.4%
1281117294000 1
 
0.4%
480118291000 1
 
0.4%
439654957000 1
 
0.4%
432980425000 1
 
0.4%
311431197000 1
 
0.4%
17106586902000 1
 
0.4%
1009951747000 1
 
0.4%
1867132300000 1
 
0.4%
978146283000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
251640500000 1
0.4%
290615485000 1
0.4%
311431197000 1
0.4%
356878000000 1
0.4%
406476872000 1
0.4%
411000000000 1
0.4%
425926504000 1
0.4%
428405373000 1
0.4%
432980425000 1
0.4%
433519109000 1
0.4%
ValueCountFrequency (%)
54791396181000 1
0.4%
50857753705000 1
0.4%
47195392438000 1
0.4%
17106586902000 1
0.4%
17076093526000 1
0.4%
14551258066000 1
0.4%
14074089995000 1
0.4%
13662462200000 1
0.4%
13065380478000 1
0.4%
11146637059000 1
0.4%

연평균증가율(%)
Real number (ℝ)

Distinct225
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7938545
Minimum-7.82
Maximum9.71
Zeros0
Zeros (%)0.0%
Negative28
Negative (%)10.2%
Memory size2.5 KiB
2023-12-11T08:06:47.302922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7.82
5-th percentile-1.557
Q10.88
median1.91
Q32.825
95-th percentile4.645
Maximum9.71
Range17.53
Interquartile range (IQR)1.945

Descriptive statistics

Standard deviation2.0947816
Coefficient of variation (CV)1.1677544
Kurtosis5.0454621
Mean1.7938545
Median Absolute Deviation (MAD)0.96
Skewness-1.0298817
Sum493.31
Variance4.3881099
MonotonicityNot monotonic
2023-12-11T08:06:47.464114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.17 4
 
1.5%
2.69 3
 
1.1%
1.26 3
 
1.1%
1.96 3
 
1.1%
1.78 3
 
1.1%
1.29 3
 
1.1%
1.77 3
 
1.1%
2.31 3
 
1.1%
2.94 2
 
0.7%
1.58 2
 
0.7%
Other values (215) 246
89.5%
ValueCountFrequency (%)
-7.82 1
0.4%
-7.64 1
0.4%
-6.8 1
0.4%
-6.36 1
0.4%
-4.94 1
0.4%
-4.62 1
0.4%
-3.05 1
0.4%
-3.02 1
0.4%
-2.25 1
0.4%
-2.1 1
0.4%
ValueCountFrequency (%)
9.71 1
0.4%
7.26 1
0.4%
7.0 1
0.4%
6.23 1
0.4%
6.13 1
0.4%
5.66 1
0.4%
5.55 1
0.4%
5.48 1
0.4%
5.46 1
0.4%
5.39 1
0.4%

Interactions

2023-12-11T08:06:42.916765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:40.624215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.218172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.620063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.033075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.487727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:43.015349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:40.685203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.282487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.687933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.094161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.556107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:43.102995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:40.749407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.347244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.752240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.158856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.623416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:43.197744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.013412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.410481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.814509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.226649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.696775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:43.291113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.084696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.475564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.884389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.305588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.768875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:43.372087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.149161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.544825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:41.960011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.394209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:42.837544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:06:47.586272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명1차년도금액(원)2차년도금액(원)3차년도금액(원)4차년도금액(원)5차년도금액(원)연평균증가율(%)
회계연도1.000NaN0.0000.0000.0000.0000.1810.228
시군명NaN1.0001.0001.0001.0001.0001.0001.000
1차년도금액(원)0.0001.0001.0001.0001.0000.9990.9880.222
2차년도금액(원)0.0001.0001.0001.0001.0000.9990.9880.222
3차년도금액(원)0.0001.0001.0001.0001.0000.9990.9900.238
4차년도금액(원)0.0001.0000.9990.9990.9991.0000.9940.242
5차년도금액(원)0.1811.0000.9880.9880.9900.9941.0000.222
연평균증가율(%)0.2281.0000.2220.2220.2380.2420.2221.000
2023-12-11T08:06:47.716025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1차년도금액(원)2차년도금액(원)3차년도금액(원)4차년도금액(원)5차년도금액(원)연평균증가율(%)회계연도
1차년도금액(원)1.0000.9960.9960.9910.9880.0490.000
2차년도금액(원)0.9961.0000.9980.9950.9930.0830.000
3차년도금액(원)0.9960.9981.0000.9970.9960.1050.000
4차년도금액(원)0.9910.9950.9971.0000.9990.1310.000
5차년도금액(원)0.9880.9930.9960.9991.0000.1540.129
연평균증가율(%)0.0490.0830.1050.1310.1541.0000.172
회계연도0.0000.0000.0000.0000.1290.1721.000

Missing values

2023-12-11T08:06:43.484601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:06:43.648812image/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

회계연도시군명자치단체명세입세출구분명1차년도금액(원)2차년도금액(원)3차년도금액(원)4차년도금액(원)5차년도금액(원)연평균증가율(%)
02023가평군경기가평군세입합계852314508000833207141000819981222000809825486000842048315000-0.3
12023경기도경기본청세입합계40272841076000407175005220004339248327600045934057866000471953924380004.05
22023고양시경기고양시세입합계41115350720004230240377000412841666800040597518440004063482758000-0.29
32023과천시경기과천시세입합계895402695000902478623000793490372000746560602000675614111000-6.8
42023광명시경기광명시세입합계135663090800015856036110001686682290000147683042300015160229910002.82
52023광주시경기광주시세입합계158711644400016847822570001765700367000174991846500017166777060001.98
62023구리시경기구리시세입합계9959584750009969655200001017044184000102966275200010469128670001.26
72023군포시경기군포시세입합계106701615300010728033700001064998398000106971644500010820566020000.35
82023김포시경기김포시세입합계209796047600022250858910002265276966000225305504700022517704380001.78
92023남양주시경기남양주시세입합계282551894800029885511590003152848637000308966137000032045724980003.2
회계연도시군명자치단체명세입세출구분명1차년도금액(원)2차년도금액(원)3차년도금액(원)4차년도금액(원)5차년도금액(원)연평균증가율(%)
2652022<NA>경기하남시세입합계124185334300012593739430001222996962000123441492800013296300830001.72
2662022<NA>경기여주시세입합계135394414100014285443650001434107436000145661440800014883075260002.39
2672022<NA>경기동두천시세입합계7779512620007794006240007956512870008066281130008192650480001.3
2682022<NA>경기과천시세입합계926549733000701949125000856458485000685958087000668845520000-7.82
2692022<NA>경기양평군세입합계959370693000981356655000993875731000101072064400010512810340002.31
2702022<NA>경기가평군세입합계6575508290006656322480006643983520006720146000006796797110000.83
2712022<NA>경기연천군세입합계7580974280007652765050007784287720007901660660008020952850001.42
2722022<NA>강원본청세입합계834760060900085562893180008770197250000898945218100092141884860002.5
2732022<NA>강원춘천시세입합계192056746700019547278940001985181706000203143965100020677815360001.86
2742022<NA>강원원주시세입합계184498181300018910836210001890251629000191077266500019396347550001.26