Overview

Dataset statistics

Number of variables23
Number of observations231
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.4 KiB
Average record size in memory205.6 B

Variable types

Categorical1
Text1
Numeric21

Dataset

Description도시림에 관련된 시군구별 세부내역을 「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 정보와
Author산림청
URLhttps://www.data.go.kr/data/15065362/fileData.do

Alerts

합계(단위 : ㎡) has 3 (1.3%) zerosZeros
소계-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 3 (1.3%) zerosZeros
산림-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 4 (1.7%) zerosZeros
산림청(국유지)-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 9 (3.9%) zerosZeros
시도(공유지)-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 13 (5.6%) zerosZeros
가로수 등 도로변 녹지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 3 (1.3%) zerosZeros
하천변 녹지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 46 (19.9%) zerosZeros
국,공유지 녹화지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 37 (16.0%) zerosZeros
학교숲-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 16 (6.9%) zerosZeros
담장녹화지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 116 (50.2%) zerosZeros
자연 휴양림 등-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 129 (55.8%) zerosZeros
자연휴양림-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 187 (81.0%) zerosZeros
산림욕장-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 149 (64.5%) zerosZeros
옥상녹화-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 118 (51.1%) zerosZeros
벽면녹화-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 123 (53.2%) zerosZeros
기타-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목 has 118 (51.1%) zerosZeros
소계-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지 has 3 (1.3%) zerosZeros
도시자연공원구역-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지 has 169 (73.2%) zerosZeros
도시공원-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지 has 6 (2.6%) zerosZeros
녹지-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지 has 34 (14.7%) zerosZeros
기타-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지 has 132 (57.1%) zerosZeros

Reproduction

Analysis started2023-12-12 07:56:11.162454
Analysis finished2023-12-12 07:56:11.408910
Duration0.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct17
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
경기
31 
서울
25 
경북
23 
전남
22 
강원
18 
Other values (12)
112 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
경기 31
13.4%
서울 25
10.8%
경북 23
10.0%
전남 22
9.5%
강원 18
7.8%
경남 18
7.8%
부산 16
6.9%
충남 15
6.5%
전북 14
 
6.1%
충북 12
 
5.2%
Other values (7) 37
16.0%

Length

2023-12-12T16:56:11.476609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 31
13.4%
서울 25
10.8%
경북 23
10.0%
전남 22
9.5%
강원 18
7.8%
경남 18
7.8%
부산 16
6.9%
충남 15
6.5%
전북 14
 
6.1%
충북 12
 
5.2%
Other values (7) 37
16.0%
Distinct209
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T16:56:11.782632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.965368
Min length2

Characters and Unicode

Total characters685
Distinct characters138
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

Unique202 ?
Unique (%)87.4%

Sample

1st row강남구
2nd row강동구
3rd row강북구
4th row강서구
5th row관악구
ValueCountFrequency (%)
동구 6
 
2.6%
중구 6
 
2.6%
서구 5
 
2.2%
북구 4
 
1.7%
남구 4
 
1.7%
고성군 2
 
0.9%
강서구 2
 
0.9%
고창군 1
 
0.4%
장수군 1
 
0.4%
무주군 1
 
0.4%
Other values (199) 199
86.1%
2023-12-12T16:56:12.274030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
12.6%
79
 
11.5%
75
 
10.9%
22
 
3.2%
20
 
2.9%
18
 
2.6%
18
 
2.6%
17
 
2.5%
16
 
2.3%
13
 
1.9%
Other values (128) 321
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 683
99.7%
Space Separator 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
 
12.6%
79
 
11.6%
75
 
11.0%
22
 
3.2%
20
 
2.9%
18
 
2.6%
18
 
2.6%
17
 
2.5%
16
 
2.3%
13
 
1.9%
Other values (127) 319
46.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 683
99.7%
Common 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
 
12.6%
79
 
11.6%
75
 
11.0%
22
 
3.2%
20
 
2.9%
18
 
2.6%
18
 
2.6%
17
 
2.5%
16
 
2.3%
13
 
1.9%
Other values (127) 319
46.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 683
99.7%
ASCII 2
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
86
 
12.6%
79
 
11.6%
75
 
11.0%
22
 
3.2%
20
 
2.9%
18
 
2.6%
18
 
2.6%
17
 
2.5%
16
 
2.3%
13
 
1.9%
Other values (127) 319
46.7%
ASCII
ValueCountFrequency (%)
2
100.0%

합계(단위 : ㎡)
Real number (ℝ)

ZEROS 

Distinct229
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52218584
Minimum0
Maximum4.5924423 × 108
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:12.442778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1491715.4
Q19278680
median28401001
Q361774750
95-th percentile2.2280181 × 108
Maximum4.5924423 × 108
Range4.5924423 × 108
Interquartile range (IQR)52496070

Descriptive statistics

Standard deviation71636492
Coefficient of variation (CV)1.3718582
Kurtosis9.2835339
Mean52218584
Median Absolute Deviation (MAD)22426205
Skewness2.7854137
Sum1.2062493 × 1010
Variance5.131787 × 1015
MonotonicityNot monotonic
2023-12-12T16:56:12.624172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
12494923.39 1
 
0.4%
64774209.6 1
 
0.4%
59959937.0 1
 
0.4%
7937587.0 1
 
0.4%
39481719.0 1
 
0.4%
23587149.2 1
 
0.4%
5504638.6 1
 
0.4%
12054625.4 1
 
0.4%
61293416.0 1
 
0.4%
Other values (219) 219
94.8%
ValueCountFrequency (%)
0.0 3
1.3%
382940.0 1
 
0.4%
410263.803 1
 
0.4%
1146554.0 1
 
0.4%
1226244.0 1
 
0.4%
1238397.0 1
 
0.4%
1309043.0 1
 
0.4%
1317841.6 1
 
0.4%
1395271.0 1
 
0.4%
1448405.8 1
 
0.4%
ValueCountFrequency (%)
459244233.0 1
0.4%
418531473.0 1
0.4%
307667231.0 1
0.4%
304868046.0 1
0.4%
283907820.0 1
0.4%
278846124.0 1
0.4%
267910995.0 1
0.4%
267366196.6 1
0.4%
266683676.0 1
0.4%
265858177.0 1
0.4%
Distinct229
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49828201
Minimum0
Maximum4.5329736 × 108
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:12.805370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile669631
Q16010897
median25438538
Q359654989
95-th percentile2.2074721 × 108
Maximum4.5329736 × 108
Range4.5329736 × 108
Interquartile range (IQR)53644092

Descriptive statistics

Standard deviation71430776
Coefficient of variation (CV)1.4335411
Kurtosis9.278496
Mean49828201
Median Absolute Deviation (MAD)22819408
Skewness2.7900556
Sum1.1510314 × 1010
Variance5.1023557 × 1015
MonotonicityNot monotonic
2023-12-12T16:56:12.976859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
7921683.0 1
 
0.4%
64446413.6 1
 
0.4%
59072814.0 1
 
0.4%
7473617.0 1
 
0.4%
37952026.0 1
 
0.4%
12106445.2 1
 
0.4%
1487316.6 1
 
0.4%
8710103.4 1
 
0.4%
59085398.0 1
 
0.4%
Other values (219) 219
94.8%
ValueCountFrequency (%)
0.0 3
1.3%
105938.4 1
 
0.4%
136879.0 1
 
0.4%
229748.0 1
 
0.4%
260145.0 1
 
0.4%
320126.6 1
 
0.4%
433780.0 1
 
0.4%
513966.6 1
 
0.4%
526276.0 1
 
0.4%
667502.0 1
 
0.4%
ValueCountFrequency (%)
453297355.0 1
0.4%
415410320.0 1
0.4%
307547802.0 1
0.4%
303944053.0 1
0.4%
283804858.0 1
0.4%
277751494.0 1
0.4%
267680514.0 1
0.4%
265115722.0 1
0.4%
263887313.0 1
0.4%
256526782.6 1
0.4%
Distinct228
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48427419
Minimum0
Maximum4.468293 × 108
Zeros4
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:13.138815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile331673
Q15674800.5
median23994029
Q358149589
95-th percentile1.9122881 × 108
Maximum4.468293 × 108
Range4.468293 × 108
Interquartile range (IQR)52474788

Descriptive statistics

Standard deviation69846542
Coefficient of variation (CV)1.4422933
Kurtosis9.6071608
Mean48427419
Median Absolute Deviation (MAD)22042553
Skewness2.8159193
Sum1.1186734 × 1010
Variance4.8785394 × 1015
MonotonicityNot monotonic
2023-12-12T16:56:13.414845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4
 
1.7%
7038363.0 1
 
0.4%
49632945.4 1
 
0.4%
56816373.0 1
 
0.4%
7219390.0 1
 
0.4%
36496782.0 1
 
0.4%
11447982.2 1
 
0.4%
1109508.6 1
 
0.4%
8429369.4 1
 
0.4%
58812809.0 1
 
0.4%
Other values (218) 218
94.4%
ValueCountFrequency (%)
0.0 4
1.7%
3300.0 1
 
0.4%
32273.0 1
 
0.4%
50293.0 1
 
0.4%
65084.0 1
 
0.4%
80000.0 1
 
0.4%
120000.0 1
 
0.4%
204425.6 1
 
0.4%
261159.0 1
 
0.4%
402187.0 1
 
0.4%
ValueCountFrequency (%)
446829298.0 1
0.4%
410815180.0 1
0.4%
307472692.0 1
0.4%
295816045.0 1
0.4%
282415477.0 1
0.4%
274460178.0 1
0.4%
265624342.0 1
0.4%
262478505.0 1
0.4%
255819287.0 1
0.4%
252996503.6 1
0.4%
Distinct223
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11408428
Minimum0
Maximum2.4865076 × 108
Zeros9
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:13.605334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16822
Q1430146.5
median1580229
Q35655803
95-th percentile56700059
Maximum2.4865076 × 108
Range2.4865076 × 108
Interquartile range (IQR)5225656.5

Descriptive statistics

Standard deviation33791273
Coefficient of variation (CV)2.9619569
Kurtosis26.601511
Mean11408428
Median Absolute Deviation (MAD)1487891
Skewness4.9255367
Sum2.635347 × 109
Variance1.1418501 × 1015
MonotonicityNot monotonic
2023-12-12T16:56:13.758731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9
 
3.9%
288363.0 1
 
0.4%
930394.0 1
 
0.4%
2500904.0 1
 
0.4%
5744295.0 1
 
0.4%
393195.0 1
 
0.4%
45415.0 1
 
0.4%
3068809.0 1
 
0.4%
2748894.0 1
 
0.4%
155712.0 1
 
0.4%
Other values (213) 213
92.2%
ValueCountFrequency (%)
0.0 9
3.9%
6744.0 1
 
0.4%
11294.0 1
 
0.4%
11641.0 1
 
0.4%
22003.0 1
 
0.4%
35937.0 1
 
0.4%
41268.0 1
 
0.4%
43043.0 1
 
0.4%
45415.0 1
 
0.4%
46875.0 1
 
0.4%
ValueCountFrequency (%)
248650759.0 1
0.4%
245409185.0 1
0.4%
185319735.0 1
0.4%
178506290.0 1
0.4%
138623948.0 1
0.4%
135054139.0 1
0.4%
112168038.0 1
0.4%
112119521.0 1
0.4%
92764240.0 1
0.4%
84135180.0 1
0.4%
Distinct219
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37018991
Minimum0
Maximum3.5406506 × 108
Zeros13
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:13.926440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11653482
median20600000
Q351666926
95-th percentile1.2245321 × 108
Maximum3.5406506 × 108
Range3.5406506 × 108
Interquartile range (IQR)50013444

Descriptive statistics

Standard deviation51464309
Coefficient of variation (CV)1.3902137
Kurtosis12.310792
Mean37018991
Median Absolute Deviation (MAD)20056325
Skewness2.9532354
Sum8.5513869 × 109
Variance2.6485751 × 1015
MonotonicityNot monotonic
2023-12-12T16:56:14.104608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 13
 
5.6%
6750000.0 1
 
0.4%
263543.0 1
 
0.4%
2943180.0 1
 
0.4%
33995878.0 1
 
0.4%
5703687.2 1
 
0.4%
716313.6 1
 
0.4%
8383954.4 1
 
0.4%
55744000.0 1
 
0.4%
43464000.0 1
 
0.4%
Other values (209) 209
90.5%
ValueCountFrequency (%)
0.0 13
5.6%
375.0 1
 
0.4%
621.0 1
 
0.4%
3300.0 1
 
0.4%
3418.0 1
 
0.4%
32273.0 1
 
0.4%
80000.0 1
 
0.4%
120000.0 1
 
0.4%
133596.0 1
 
0.4%
141254.0 1
 
0.4%
ValueCountFrequency (%)
354065058.0 1
0.4%
326680000.0 1
0.4%
263318991.0 1
0.4%
237703736.6 1
0.4%
233980000.0 1
0.4%
151919689.0 1
0.4%
144980399.0 1
0.4%
143651249.0 1
0.4%
138473236.1 1
0.4%
136320000.0 1
0.4%
Distinct229
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean142241.18
Minimum0
Maximum2859312
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:14.261084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9002
Q135495
median80498
Q3181433
95-th percentile421450.45
Maximum2859312
Range2859312
Interquartile range (IQR)145938

Descriptive statistics

Standard deviation230057.4
Coefficient of variation (CV)1.6173755
Kurtosis85.39134
Mean142241.18
Median Absolute Deviation (MAD)56998
Skewness7.769354
Sum32857713
Variance5.2926408 × 1010
MonotonicityNot monotonic
2023-12-12T16:56:14.438296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
499274.0 1
 
0.4%
37328.0 1
 
0.4%
65520.0 1
 
0.4%
32924.0 1
 
0.4%
5937.0 1
 
0.4%
371370.0 1
 
0.4%
145897.0 1
 
0.4%
137496.0 1
 
0.4%
83188.0 1
 
0.4%
Other values (219) 219
94.8%
ValueCountFrequency (%)
0.0 3
1.3%
3336.0 1
 
0.4%
3387.0 1
 
0.4%
3436.0 1
 
0.4%
5937.0 1
 
0.4%
6493.0 1
 
0.4%
6800.0 1
 
0.4%
7175.0 1
 
0.4%
8656.0 1
 
0.4%
8840.0 1
 
0.4%
ValueCountFrequency (%)
2859312.0 1
0.4%
920439.0 1
0.4%
869906.0 1
0.4%
749965.0 1
0.4%
629130.5 1
0.4%
559344.0 1
0.4%
538329.0 1
0.4%
515025.0 1
0.4%
499274.0 1
0.4%
471506.0 1
0.4%
Distinct181
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69904.654
Minimum0
Maximum1869400
Zeros46
Zeros (%)19.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:14.573385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11000
median13072
Q346616.5
95-th percentile322443.5
Maximum1869400
Range1869400
Interquartile range (IQR)45616.5

Descriptive statistics

Standard deviation193818.07
Coefficient of variation (CV)2.7726061
Kurtosis46.217059
Mean69904.654
Median Absolute Deviation (MAD)13072
Skewness6.179056
Sum16147975
Variance3.7565443 × 1010
MonotonicityNot monotonic
2023-12-12T16:56:14.768341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46
 
19.9%
1000 2
 
0.9%
7800 2
 
0.9%
2000 2
 
0.9%
9936 2
 
0.9%
15000 2
 
0.9%
1507 1
 
0.4%
116886 1
 
0.4%
11520 1
 
0.4%
20877 1
 
0.4%
Other values (171) 171
74.0%
ValueCountFrequency (%)
0 46
19.9%
200 1
 
0.4%
212 1
 
0.4%
301 1
 
0.4%
342 1
 
0.4%
400 1
 
0.4%
500 1
 
0.4%
508 1
 
0.4%
650 1
 
0.4%
676 1
 
0.4%
ValueCountFrequency (%)
1869400 1
0.4%
1429000 1
0.4%
1144706 1
0.4%
699876 1
0.4%
572000 1
0.4%
544290 1
0.4%
437332 1
0.4%
431420 1
0.4%
360240 1
0.4%
352100 1
0.4%
Distinct193
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95177.6
Minimum0
Maximum1353090
Zeros37
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:14.948353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15157.5
median34200
Q3107841
95-th percentile346330
Maximum1353090
Range1353090
Interquartile range (IQR)102683.5

Descriptive statistics

Standard deviation178580.41
Coefficient of variation (CV)1.8762861
Kurtosis19.388752
Mean95177.6
Median Absolute Deviation (MAD)34200
Skewness4.027395
Sum21986026
Variance3.1890962 × 1010
MonotonicityNot monotonic
2023-12-12T16:56:15.431652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 37
 
16.0%
1200.0 2
 
0.9%
2000.0 2
 
0.9%
19088.0 1
 
0.4%
188934.0 1
 
0.4%
155645.0 1
 
0.4%
4300.0 1
 
0.4%
107166.0 1
 
0.4%
215878.0 1
 
0.4%
100734.0 1
 
0.4%
Other values (183) 183
79.2%
ValueCountFrequency (%)
0.0 37
16.0%
224.0 1
 
0.4%
600.0 1
 
0.4%
1100.0 1
 
0.4%
1200.0 2
 
0.9%
1808.0 1
 
0.4%
2000.0 2
 
0.9%
2344.0 1
 
0.4%
2600.0 1
 
0.4%
2984.0 1
 
0.4%
ValueCountFrequency (%)
1353090.0 1
0.4%
1075120.0 1
0.4%
978273.0 1
0.4%
858728.0 1
0.4%
823890.0 1
0.4%
763700.0 1
0.4%
644552.0 1
0.4%
602589.0 1
0.4%
589758.0 1
0.4%
384686.0 1
0.4%
Distinct207
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33071.584
Minimum0
Maximum780000
Zeros16
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:15.620723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14970
median15931
Q337190
95-th percentile97083
Maximum780000
Range780000
Interquartile range (IQR)32220

Descriptive statistics

Standard deviation74430.874
Coefficient of variation (CV)2.250599
Kurtosis66.659923
Mean33071.584
Median Absolute Deviation (MAD)13141
Skewness7.4764556
Sum7639535.8
Variance5.5399551 × 109
MonotonicityNot monotonic
2023-12-12T16:56:15.784754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
6.9%
16500.0 3
 
1.3%
1000.0 3
 
1.3%
12500.0 2
 
0.9%
10000.0 2
 
0.9%
32548.0 2
 
0.9%
34540.0 2
 
0.9%
6500.0 2
 
0.9%
35455.0 1
 
0.4%
20844.0 1
 
0.4%
Other values (197) 197
85.3%
ValueCountFrequency (%)
0.0 16
6.9%
100.0 1
 
0.4%
240.0 1
 
0.4%
320.0 1
 
0.4%
560.0 1
 
0.4%
700.0 1
 
0.4%
1000.0 3
 
1.3%
1034.0 1
 
0.4%
1040.0 1
 
0.4%
1100.0 1
 
0.4%
ValueCountFrequency (%)
780000.0 1
0.4%
666970.0 1
0.4%
272235.0 1
0.4%
247787.0 1
0.4%
173823.0 1
0.4%
170000.0 1
0.4%
146421.0 1
0.4%
117872.0 1
0.4%
108162.0 1
0.4%
100973.0 1
0.4%
Distinct107
Distinct (%)46.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7604.0736
Minimum0
Maximum650000
Zeros116
Zeros (%)50.2%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:15.939383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35105
95-th percentile27469.5
Maximum650000
Range650000
Interquartile range (IQR)5105

Descriptive statistics

Standard deviation43634.577
Coefficient of variation (CV)5.7383159
Kurtosis206.64201
Mean7604.0736
Median Absolute Deviation (MAD)0
Skewness14.024549
Sum1756541
Variance1.9039763 × 109
MonotonicityNot monotonic
2023-12-12T16:56:16.080230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 116
50.2%
2000 3
 
1.3%
4000 2
 
0.9%
1400 2
 
0.9%
9000 2
 
0.9%
150 2
 
0.9%
2500 2
 
0.9%
1500 2
 
0.9%
500 2
 
0.9%
5752 1
 
0.4%
Other values (97) 97
42.0%
ValueCountFrequency (%)
0 116
50.2%
92 1
 
0.4%
116 1
 
0.4%
150 2
 
0.9%
200 1
 
0.4%
300 1
 
0.4%
400 1
 
0.4%
425 1
 
0.4%
450 1
 
0.4%
500 2
 
0.9%
ValueCountFrequency (%)
650000 1
0.4%
65026 1
0.4%
57200 1
0.4%
47212 1
0.4%
45500 1
0.4%
43253 1
0.4%
40028 1
0.4%
36500 1
0.4%
36000 1
0.4%
35123 1
0.4%
Distinct93
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean985144.67
Minimum0
Maximum91988966
Zeros129
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:16.249754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3500000
95-th percentile3286500
Maximum91988966
Range91988966
Interquartile range (IQR)500000

Descriptive statistics

Standard deviation6168641
Coefficient of variation (CV)6.26166
Kurtosis208.40614
Mean985144.67
Median Absolute Deviation (MAD)0
Skewness14.119058
Sum2.2756842 × 108
Variance3.8052132 × 1013
MonotonicityNot monotonic
2023-12-12T16:56:16.400671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 129
55.8%
150000 3
 
1.3%
50000 3
 
1.3%
500000 3
 
1.3%
980000 2
 
0.9%
1000000 2
 
0.9%
400000 2
 
0.9%
370000 2
 
0.9%
3148775 1
 
0.4%
324015 1
 
0.4%
Other values (83) 83
35.9%
ValueCountFrequency (%)
0 129
55.8%
7467 1
 
0.4%
23000 1
 
0.4%
41000 1
 
0.4%
50000 3
 
1.3%
53653 1
 
0.4%
55800 1
 
0.4%
59000 1
 
0.4%
77000 1
 
0.4%
94000 1
 
0.4%
ValueCountFrequency (%)
91988966 1
0.4%
11864100 1
0.4%
7645802 1
0.4%
6130000 1
0.4%
6080000 1
0.4%
5180000 1
0.4%
4365447 1
0.4%
4290000 1
0.4%
4282300 1
0.4%
3789268 1
0.4%
Distinct44
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean741735.43
Minimum0
Maximum91918966
Zeros187
Zeros (%)81.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:16.563884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2347425
Maximum91918966
Range91918966
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6134258
Coefficient of variation (CV)8.2701428
Kurtosis214.83723
Mean741735.43
Median Absolute Deviation (MAD)0
Skewness14.435456
Sum1.7134088 × 108
Variance3.7629121 × 1013
MonotonicityNot monotonic
2023-12-12T16:56:16.721786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 187
81.0%
1200000 2
 
0.9%
2750000 1
 
0.4%
1200248 1
 
0.4%
405274 1
 
0.4%
4810000 1
 
0.4%
1300000 1
 
0.4%
1920000 1
 
0.4%
1350000 1
 
0.4%
324015 1
 
0.4%
Other values (34) 34
 
14.7%
ValueCountFrequency (%)
0 187
81.0%
7467 1
 
0.4%
311000 1
 
0.4%
314000 1
 
0.4%
324015 1
 
0.4%
358048 1
 
0.4%
370000 1
 
0.4%
405274 1
 
0.4%
433135 1
 
0.4%
436660 1
 
0.4%
ValueCountFrequency (%)
91918966 1
0.4%
11864100 1
0.4%
7332746 1
0.4%
4810000 1
0.4%
3630000 1
0.4%
3363000 1
0.4%
3210000 1
0.4%
3051187 1
0.4%
2750000 1
0.4%
2600000 1
0.4%
Distinct70
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean243409.23
Minimum0
Maximum6130000
Zeros149
Zeros (%)64.5%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:16.858880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3150000
95-th percentile1300000
Maximum6130000
Range6130000
Interquartile range (IQR)150000

Descriptive statistics

Standard deviation666469.7
Coefficient of variation (CV)2.7380625
Kurtosis34.914299
Mean243409.23
Median Absolute Deviation (MAD)0
Skewness5.2022151
Sum56227533
Variance4.4418186 × 1011
MonotonicityNot monotonic
2023-12-12T16:56:17.006601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 149
64.5%
150000 4
 
1.7%
370000 3
 
1.3%
500000 3
 
1.3%
100000 3
 
1.3%
50000 3
 
1.3%
400000 2
 
0.9%
1000000 2
 
0.9%
920000 1
 
0.4%
23000 1
 
0.4%
Other values (60) 60
26.0%
ValueCountFrequency (%)
0 149
64.5%
23000 1
 
0.4%
40000 1
 
0.4%
41000 1
 
0.4%
50000 3
 
1.3%
53653 1
 
0.4%
55800 1
 
0.4%
59000 1
 
0.4%
70000 1
 
0.4%
77000 1
 
0.4%
ValueCountFrequency (%)
6130000 1
0.4%
4365447 1
0.4%
3480000 1
0.4%
2520000 1
0.4%
2260000 1
0.4%
2000000 1
0.4%
1981730 1
0.4%
1740000 1
0.4%
1481000 1
0.4%
1400000 1
0.4%
Distinct105
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2722.4225
Minimum0
Maximum63053
Zeros118
Zeros (%)51.1%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:17.147663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32465.5
95-th percentile13025.5
Maximum63053
Range63053
Interquartile range (IQR)2465.5

Descriptive statistics

Standard deviation6697.4892
Coefficient of variation (CV)2.4601211
Kurtosis38.629494
Mean2722.4225
Median Absolute Deviation (MAD)0
Skewness5.3767885
Sum628879.6
Variance44856361
MonotonicityNot monotonic
2023-12-12T16:56:17.303701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 118
51.1%
800.0 4
 
1.7%
200.0 3
 
1.3%
100.0 2
 
0.9%
500.0 2
 
0.9%
2500.0 2
 
0.9%
1400.0 2
 
0.9%
5373.0 1
 
0.4%
1117.0 1
 
0.4%
688.0 1
 
0.4%
Other values (95) 95
41.1%
ValueCountFrequency (%)
0.0 118
51.1%
63.0 1
 
0.4%
100.0 2
 
0.9%
120.0 1
 
0.4%
139.0 1
 
0.4%
172.0 1
 
0.4%
200.0 3
 
1.3%
213.0 1
 
0.4%
249.0 1
 
0.4%
250.0 1
 
0.4%
ValueCountFrequency (%)
63053.0 1
0.4%
48861.0 1
0.4%
29000.0 1
0.4%
22713.0 1
0.4%
22130.0 1
0.4%
17196.0 1
0.4%
16979.0 1
0.4%
15271.0 1
0.4%
14888.0 1
0.4%
14071.0 1
0.4%
Distinct105
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2796.69
Minimum0
Maximum67707
Zeros123
Zeros (%)53.2%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:17.486169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32062.5
95-th percentile13379.5
Maximum67707
Range67707
Interquartile range (IQR)2062.5

Descriptive statistics

Standard deviation7589.7603
Coefficient of variation (CV)2.7138368
Kurtosis34.152698
Mean2796.69
Median Absolute Deviation (MAD)0
Skewness5.2505038
Sum646035.4
Variance57604462
MonotonicityNot monotonic
2023-12-12T16:56:17.675651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 123
53.2%
100.0 4
 
1.7%
300.0 2
 
0.9%
1832.0 1
 
0.4%
1278.0 1
 
0.4%
5000.0 1
 
0.4%
47200.0 1
 
0.4%
957.0 1
 
0.4%
6504.0 1
 
0.4%
27000.0 1
 
0.4%
Other values (95) 95
41.1%
ValueCountFrequency (%)
0.0 123
53.2%
50.0 1
 
0.4%
96.0 1
 
0.4%
100.0 4
 
1.7%
107.0 1
 
0.4%
117.0 1
 
0.4%
120.0 1
 
0.4%
157.0 1
 
0.4%
160.0 1
 
0.4%
174.0 1
 
0.4%
ValueCountFrequency (%)
67707.0 1
0.4%
49359.0 1
0.4%
47200.0 1
0.4%
27000.0 1
0.4%
26462.0 1
0.4%
25210.0 1
0.4%
24715.0 1
0.4%
16835.0 1
0.4%
15070.0 1
0.4%
14925.0 1
0.4%
Distinct114
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62118.841
Minimum0
Maximum1321126
Zeros118
Zeros (%)51.1%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:17.862499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q329065
95-th percentile323209.5
Maximum1321126
Range1321126
Interquartile range (IQR)29065

Descriptive statistics

Standard deviation167118.5
Coefficient of variation (CV)2.6903029
Kurtosis24.73187
Mean62118.841
Median Absolute Deviation (MAD)0
Skewness4.5030138
Sum14349452
Variance2.7928592 × 1010
MonotonicityNot monotonic
2023-12-12T16:56:18.035368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 118
51.1%
24154.0 1
 
0.4%
26500.0 1
 
0.4%
850.0 1
 
0.4%
12000.0 1
 
0.4%
12240.0 1
 
0.4%
13878.0 1
 
0.4%
8478.0 1
 
0.4%
240.0 1
 
0.4%
2560.0 1
 
0.4%
Other values (104) 104
45.0%
ValueCountFrequency (%)
0.0 118
51.1%
1.0 1
 
0.4%
168.0 1
 
0.4%
240.0 1
 
0.4%
560.0 1
 
0.4%
600.0 1
 
0.4%
850.0 1
 
0.4%
900.0 1
 
0.4%
1000.0 1
 
0.4%
1500.0 1
 
0.4%
ValueCountFrequency (%)
1321126.0 1
0.4%
1172575.0 1
0.4%
779344.0 1
0.4%
737601.0 1
0.4%
623592.0 1
0.4%
578033.0 1
0.4%
545727.0 1
0.4%
504700.0 1
0.4%
483032.0 1
0.4%
398247.0 1
0.4%
Distinct229
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2390382.4
Minimum0
Maximum46651563
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:18.198893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile59739.5
Q1420906.7
median1110371
Q32982131.6
95-th percentile8448043.5
Maximum46651563
Range46651563
Interquartile range (IQR)2561224.9

Descriptive statistics

Standard deviation3974616.7
Coefficient of variation (CV)1.6627535
Kurtosis67.320367
Mean2390382.4
Median Absolute Deviation (MAD)869686.2
Skewness6.6603424
Sum5.5217832 × 108
Variance1.5797578 × 1013
MonotonicityNot monotonic
2023-12-12T16:56:18.341066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
4573240.39 1
 
0.4%
327796.0 1
 
0.4%
887123.0 1
 
0.4%
463970.0 1
 
0.4%
1529693.0 1
 
0.4%
11480704.0 1
 
0.4%
4017322.0 1
 
0.4%
3344522.0 1
 
0.4%
2208018.0 1
 
0.4%
Other values (219) 219
94.8%
ValueCountFrequency (%)
0.0 3
1.3%
576.0 1
 
0.4%
5207.0 1
 
0.4%
9200.0 1
 
0.4%
13254.0 1
 
0.4%
14897.0 1
 
0.4%
16533.0 1
 
0.4%
44294.0 1
 
0.4%
48288.0 1
 
0.4%
56396.0 1
 
0.4%
ValueCountFrequency (%)
46651563.0 1
0.4%
16925186.05 1
0.4%
13873368.0 1
0.4%
11480704.0 1
0.4%
10839414.0 1
0.4%
9803710.0 1
0.4%
9361612.1 1
0.4%
9266782.16 1
0.4%
9161460.0 1
0.4%
8893176.89 1
0.4%
Distinct63
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean683149.85
Minimum0
Maximum38414124
Zeros169
Zeros (%)73.2%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:18.465669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q371003
95-th percentile3110768.5
Maximum38414124
Range38414124
Interquartile range (IQR)71003

Descriptive statistics

Standard deviation2940234.8
Coefficient of variation (CV)4.3039383
Kurtosis120.4934
Mean683149.85
Median Absolute Deviation (MAD)0
Skewness9.9720697
Sum1.5780762 × 108
Variance8.6449807 × 1012
MonotonicityNot monotonic
2023-12-12T16:56:18.635535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 169
73.2%
2449752.0 1
 
0.4%
149640.0 1
 
0.4%
2525372.0 1
 
0.4%
2876.0 1
 
0.4%
1093989.0 1
 
0.4%
38414124.0 1
 
0.4%
1702510.0 1
 
0.4%
1739960.0 1
 
0.4%
622667.0 1
 
0.4%
Other values (53) 53
 
22.9%
ValueCountFrequency (%)
0.0 169
73.2%
2876.0 1
 
0.4%
11306.0 1
 
0.4%
33000.0 1
 
0.4%
33181.0 1
 
0.4%
108825.0 1
 
0.4%
149640.0 1
 
0.4%
190630.0 1
 
0.4%
197841.0 1
 
0.4%
215000.0 1
 
0.4%
ValueCountFrequency (%)
38414124.0 1
0.4%
13026000.0 1
0.4%
11149112.0 1
0.4%
8482875.0 1
0.4%
7215651.0 1
0.4%
5660000.0 1
0.4%
4595439.0 1
0.4%
3838000.0 1
0.4%
3568693.0 1
0.4%
3452944.0 1
0.4%
Distinct226
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1144823
Minimum0
Maximum10522347
Zeros6
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:18.829873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25880.5
Q1213977
median505811
Q31455805
95-th percentile4472168
Maximum10522347
Range10522347
Interquartile range (IQR)1241828

Descriptive statistics

Standard deviation1558111.5
Coefficient of variation (CV)1.3610065
Kurtosis7.7919958
Mean1144823
Median Absolute Deviation (MAD)388113.1
Skewness2.4924259
Sum2.6445411 × 108
Variance2.4277115 × 1012
MonotonicityNot monotonic
2023-12-12T16:56:18.976435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6
 
2.6%
1821293.59 1
 
0.4%
262662.0 1
 
0.4%
370616.0 1
 
0.4%
66243.0 1
 
0.4%
398474.0 1
 
0.4%
328019.0 1
 
0.4%
107318.0 1
 
0.4%
10522347.0 1
 
0.4%
1432339.0 1
 
0.4%
Other values (216) 216
93.5%
ValueCountFrequency (%)
0.0 6
2.6%
1320.0 1
 
0.4%
3597.0 1
 
0.4%
13254.0 1
 
0.4%
14897.0 1
 
0.4%
16201.0 1
 
0.4%
22149.0 1
 
0.4%
29612.0 1
 
0.4%
30561.0 1
 
0.4%
33000.0 1
 
0.4%
ValueCountFrequency (%)
10522347.0 1
0.4%
7007823.0 1
0.4%
6881873.0 1
0.4%
6516046.16 1
0.4%
6197533.0 1
0.4%
6179303.0 1
0.4%
5906218.36 1
0.4%
5112892.0 1
0.4%
4878150.0 1
0.4%
4647478.1 1
0.4%
Distinct198
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean385982.43
Minimum0
Maximum4304106
Zeros34
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:19.127452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113383
median136548
Q3484894.9
95-th percentile1540891.1
Maximum4304106
Range4304106
Interquartile range (IQR)471511.9

Descriptive statistics

Standard deviation628515.31
Coefficient of variation (CV)1.6283521
Kurtosis14.367095
Mean385982.43
Median Absolute Deviation (MAD)136548
Skewness3.2915403
Sum89161942
Variance3.9503149 × 1011
MonotonicityNot monotonic
2023-12-12T16:56:19.251615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 34
 
14.7%
228087.0 1
 
0.4%
391729.0 1
 
0.4%
452491.7 1
 
0.4%
414800.0 1
 
0.4%
104070.0 1
 
0.4%
16200.0 1
 
0.4%
555641.0 1
 
0.4%
172100.0 1
 
0.4%
13217.0 1
 
0.4%
Other values (188) 188
81.4%
ValueCountFrequency (%)
0.0 34
14.7%
100.0 1
 
0.4%
576.0 1
 
0.4%
772.0 1
 
0.4%
2110.0 1
 
0.4%
2374.0 1
 
0.4%
2647.0 1
 
0.4%
2922.0 1
 
0.4%
3296.0 1
 
0.4%
3348.0 1
 
0.4%
ValueCountFrequency (%)
4304106.0 1
0.4%
3932937.0 1
0.4%
3831591.0 1
0.4%
2606205.0 1
0.4%
2357067.0 1
0.4%
2107116.8 1
0.4%
1701264.0 1
0.4%
1629185.0 1
0.4%
1588084.4 1
0.4%
1582711.0 1
0.4%
Distinct100
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176427.09
Minimum0
Maximum6525783
Zeros132
Zeros (%)57.1%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:56:19.379079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q324877
95-th percentile1139728
Maximum6525783
Range6525783
Interquartile range (IQR)24877

Descriptive statistics

Standard deviation641259.99
Coefficient of variation (CV)3.6347026
Kurtosis51.866314
Mean176427.09
Median Absolute Deviation (MAD)0
Skewness6.4813209
Sum40754658
Variance4.1121438 × 1011
MonotonicityNot monotonic
2023-12-12T16:56:19.930307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 132
57.1%
1308307.6 1
 
0.4%
19282.0 1
 
0.4%
999912.0 1
 
0.4%
26567.0 1
 
0.4%
583.0 1
 
0.4%
1811.0 1
 
0.4%
8562.0 1
 
0.4%
45512.0 1
 
0.4%
1604.0 1
 
0.4%
Other values (90) 90
39.0%
ValueCountFrequency (%)
0.0 132
57.1%
100.0 1
 
0.4%
221.0 1
 
0.4%
230.0 1
 
0.4%
583.0 1
 
0.4%
767.0 1
 
0.4%
1240.0 1
 
0.4%
1454.0 1
 
0.4%
1604.0 1
 
0.4%
1700.0 1
 
0.4%
ValueCountFrequency (%)
6525783.0 1
0.4%
4268033.0 1
0.4%
3567100.0 1
0.4%
2357067.0 1
0.4%
1709610.0 1
0.4%
1674446.0 1
0.4%
1308307.6 1
0.4%
1263917.0 1
0.4%
1194609.0 1
0.4%
1186645.0 1
0.4%

Sample

시도시군구합계(단위 : ㎡)소계-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목산림-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목산림청(국유지)-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목시도(공유지)-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목가로수 등 도로변 녹지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목하천변 녹지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목국,공유지 녹화지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목학교숲-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목담장녹화지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목자연 휴양림 등-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목자연휴양림-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목산림욕장-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목옥상녹화-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목벽면녹화-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목기타-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목소계-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지도시자연공원구역-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지도시공원-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지녹지-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지기타-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지
0서울강남구12494923.397921683.07038363.0288363.06750000.0499274.024077119088.083313.0000014888.01832.024154.04573240.392449752.01821293.59302194.80.0
1서울강동구5896458.04280469.02993043.043043.02950000.0252291.0699876118740.066387.01354000015271.02891.0118430.01615989.0624597.0862091.0129301.00.0
2서울강북구10984814.09343368.09257547.08996985.0260562.037354.040905511.031366.019850005051.0464.00.01641446.0108825.01508436.021317.02868.0
3서울강서구6393579.04101976.03969388.0109388.03860000.066955.000.054688.000007856.0782.02307.02291603.00.01900040.0389693.01870.0
4서울관악구7470633.02619130.02397999.01002583.01395416.080488.0260000.038710.021000005835.05098.062900.04851503.04595439.0252768.03296.00.0
5서울광진구3844377.0851885.0508093.068093.0440000.074198.014198820383.040661.049500008815.02063.050734.02992492.02307085.0666361.019046.00.0
6서울구로구1238397.0667502.0402187.072187.0330000.069046.0714590.040947.0115000009629.02305.060429.0570895.00.0502412.063892.04591.0
7서울금천구2985922.01097105.0760776.0251475.0509301.0103511.01541220.016368.0900500000500008935.02493.00.01888817.01796159.045879.042456.04323.0
8서울노원구14289697.05988506.05622040.05231019.0391021.057852.027045140000.086751.03366200010486.010670.00.08301191.07215651.0857031.0210123.018386.0
9서울도봉구2950855.01697814.01501436.0339901.01161535.048600.0423004900.039803.0106950004735.05876.039469.01253041.00.01185569.028103.039369.0
시도시군구합계(단위 : ㎡)소계-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목산림-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목산림청(국유지)-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목시도(공유지)-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목가로수 등 도로변 녹지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목하천변 녹지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목국,공유지 녹화지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목학교숲-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목담장녹화지-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목자연 휴양림 등-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목자연휴양림-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목산림욕장-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목옥상녹화-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목벽면녹화-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목기타-「산림자원의 조성 및 관리에 관한 법률」에 의한 산림과 수목소계-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지도시자연공원구역-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지도시공원-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지녹지-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지기타-「도시공원 및 녹지 등에 관한 법률」에 의한 공원녹지
221경남창녕군4758163.04660546.03400839.02660839.0740000.030992.0254367177948.04900.007500000750000800.00.040700.097617.00.064017.00.033600.0
222경남고성군12356821.011532204.010664788.0749788.09915000.0128000.0591620900.012500.0070000007000000.0100.00.0824617.00.0726760.097857.00.0
223경남남해군1146554.01001895.0879095.0879095.00.06800.020009000.011000.00940000940000.00.00.0144659.00.0144659.00.00.0
224경남하동군2652165.02334193.01814141.0454310.01359831.033567.0280001200.016500.0250043313543313502500.02650.00.0317972.00.0317972.00.00.0
225경남산청군5205182.05156894.03663806.03277806.0386000.022388.0078100.01000.06300136000012600001000000.00.025300.048288.00.048288.00.00.0
226경남함양군46685107.046381555.042984395.08873655.034110740.0128504.0993619700.018020.010500321000032100000500.00.00.0303552.00.0303552.00.00.0
227경남거창군1448405.81287765.0987930.0743280.0244650.0248290.0393443250.08251.0400000250.050.00.0160640.80.0154652.80.05988.0
228경남합천군3016161.02838361.02501660.02501660.00.081600.038000199160.012041.01500000200.03200.01000.0177800.00.0177800.00.00.0
229제주제주시459244233.0453297355.0446829298.092764240.0354065058.0157963.029780157011.017872.006080000260000034800009295.04736.011400.05946878.00.05112892.0367730.0466256.0
230제주서귀포시418531473.0415410320.0410815180.084135180.0326680000.0187400.0400064160.016500.004290000255000017400003050.00.030030.03121153.00.01419889.01701264.00.0