Overview

Dataset statistics

Number of variables20
Number of observations1336
Missing cells22470
Missing cells (%)84.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory218.0 KiB
Average record size in memory167.1 B

Variable types

Numeric2
Categorical1
Unsupported15
Text2

Dataset

Description국립세종수목원 이산화탄소 흡수에 관한 자료입니다.이팝나무,메타세쿼이아, 칠엽수, 소나무 4종에 관한 정보를 담고 있습니다.
Author한국수목원정원관리원
URLhttps://www.data.go.kr/data/15126709/fileData.do

Alerts

no is highly overall correlated with 수종 High correlation
수종 is highly overall correlated with noHigh correlation
Unnamed: 3 has 1336 (100.0%) missing valuesMissing
Unnamed: 4 has 1336 (100.0%) missing valuesMissing
Unnamed: 5 has 1336 (100.0%) missing valuesMissing
Unnamed: 6 has 1333 (99.8%) missing valuesMissing
Unnamed: 7 has 1316 (98.5%) missing valuesMissing
Unnamed: 8 has 1318 (98.7%) missing valuesMissing
Unnamed: 9 has 1318 (98.7%) missing valuesMissing
Unnamed: 10 has 1314 (98.4%) missing valuesMissing
Unnamed: 11 has 1313 (98.3%) missing valuesMissing
Unnamed: 12 has 1336 (100.0%) missing valuesMissing
Unnamed: 13 has 1336 (100.0%) missing valuesMissing
Unnamed: 14 has 1334 (99.9%) missing valuesMissing
Unnamed: 15 has 1308 (97.9%) missing valuesMissing
Unnamed: 16 has 1310 (98.1%) missing valuesMissing
Unnamed: 17 has 1310 (98.1%) missing valuesMissing
Unnamed: 18 has 1308 (97.9%) missing valuesMissing
Unnamed: 19 has 1308 (97.9%) missing valuesMissing
no has unique valuesUnique
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 16 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 17 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 18 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 19 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 13:31:00.990137
Analysis finished2024-03-14 13:31:04.131369
Duration3.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

no
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean668.5
Minimum1
Maximum1336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-03-14T22:31:04.358995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile67.75
Q1334.75
median668.5
Q31002.25
95-th percentile1269.25
Maximum1336
Range1335
Interquartile range (IQR)667.5

Descriptive statistics

Standard deviation385.81429
Coefficient of variation (CV)0.57713432
Kurtosis-1.2
Mean668.5
Median Absolute Deviation (MAD)334
Skewness0
Sum893116
Variance148852.67
MonotonicityStrictly increasing
2024-03-14T22:31:04.815558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
899 1
 
0.1%
897 1
 
0.1%
896 1
 
0.1%
895 1
 
0.1%
894 1
 
0.1%
893 1
 
0.1%
892 1
 
0.1%
891 1
 
0.1%
890 1
 
0.1%
Other values (1326) 1326
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1336 1
0.1%
1335 1
0.1%
1334 1
0.1%
1333 1
0.1%
1332 1
0.1%
1331 1
0.1%
1330 1
0.1%
1329 1
0.1%
1328 1
0.1%
1327 1
0.1%

수종
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
소나무
794 
메타세쿼이아
216 
칠엽수
172 
이팝나무
154 

Length

Max length6
Median length3
Mean length3.6002994
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소나무 794
59.4%
메타세쿼이아 216
 
16.2%
칠엽수 172
 
12.9%
이팝나무 154
 
11.5%

Length

2024-03-14T22:31:05.262498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:31:05.596314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소나무 794
59.4%
메타세쿼이아 216
 
16.2%
칠엽수 172
 
12.9%
이팝나무 154
 
11.5%

흉고직경(DBH)
Real number (ℝ)

Distinct266
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.74396
Minimum5.5
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-03-14T22:31:05.960910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile8.3
Q111.1
median13.3
Q317.925
95-th percentile31
Maximum78
Range72.5
Interquartile range (IQR)6.825

Descriptive statistics

Standard deviation7.2376724
Coefficient of variation (CV)0.45971106
Kurtosis4.522285
Mean15.74396
Median Absolute Deviation (MAD)2.5
Skewness1.6301958
Sum21033.93
Variance52.383902
MonotonicityNot monotonic
2024-03-14T22:31:06.606862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.0 28
 
2.1%
11.0 22
 
1.6%
11.1 21
 
1.6%
11.2 20
 
1.5%
12.4 20
 
1.5%
12.3 19
 
1.4%
11.4 19
 
1.4%
14.0 19
 
1.4%
10.3 18
 
1.3%
14.2 18
 
1.3%
Other values (256) 1132
84.7%
ValueCountFrequency (%)
5.5 4
0.3%
5.7 1
 
0.1%
5.8 4
0.3%
5.9 1
 
0.1%
6.0 3
0.2%
6.1 4
0.3%
6.2 1
 
0.1%
6.25 1
 
0.1%
6.3 2
0.1%
6.4 1
 
0.1%
ValueCountFrequency (%)
78.0 1
0.1%
41.5 1
0.1%
40.8 1
0.1%
39.8 1
0.1%
39.4 1
0.1%
38.9 1
0.1%
38.8 1
0.1%
38.6 2
0.1%
38.2 1
0.1%
37.8 1
0.1%

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1336
Missing (%)100.0%
Memory size11.9 KiB

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1336
Missing (%)100.0%
Memory size11.9 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1336
Missing (%)100.0%
Memory size11.9 KiB

Unnamed: 6
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing1333
Missing (%)99.8%
Memory size10.6 KiB
2024-03-14T22:31:07.309394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length6
Mean length15.333333
Min length4

Characters and Unicode

Total characters46
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row이팝나무
2nd row메타세쿼이아
3rd row* 이산화탄소흡수량은 30년간 총 이산화탄소흡수량을 산정한 결과임
ValueCountFrequency (%)
이팝나무 1
11.1%
메타세쿼이아 1
11.1%
1
11.1%
이산화탄소흡수량은 1
11.1%
30년간 1
11.1%
총 1
11.1%
이산화탄소흡수량을 1
11.1%
산정한 1
11.1%
결과임 1
11.1%
2024-03-14T22:31:08.390358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
13.0%
이 4
 
8.7%
산 3
 
6.5%
량 2
 
4.3%
수 2
 
4.3%
소 2
 
4.3%
탄 2
 
4.3%
화 2
 
4.3%
흡 2
 
4.3%
* 1
 
2.2%
Other values (20) 20
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37
80.4%
Space Separator 6
 
13.0%
Decimal Number 2
 
4.3%
Other Punctuation 1
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 4
 
10.8%
산 3
 
8.1%
량 2
 
5.4%
수 2
 
5.4%
소 2
 
5.4%
탄 2
 
5.4%
화 2
 
5.4%
흡 2
 
5.4%
과 1
 
2.7%
결 1
 
2.7%
Other values (16) 16
43.2%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37
80.4%
Common 9
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 4
 
10.8%
산 3
 
8.1%
량 2
 
5.4%
수 2
 
5.4%
소 2
 
5.4%
탄 2
 
5.4%
화 2
 
5.4%
흡 2
 
5.4%
과 1
 
2.7%
결 1
 
2.7%
Other values (16) 16
43.2%
Common
ValueCountFrequency (%)
6
66.7%
* 1
 
11.1%
0 1
 
11.1%
3 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37
80.4%
ASCII 9
 
19.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
66.7%
* 1
 
11.1%
0 1
 
11.1%
3 1
 
11.1%
Hangul
ValueCountFrequency (%)
이 4
 
10.8%
산 3
 
8.1%
량 2
 
5.4%
수 2
 
5.4%
소 2
 
5.4%
탄 2
 
5.4%
화 2
 
5.4%
흡 2
 
5.4%
과 1
 
2.7%
결 1
 
2.7%
Other values (16) 16
43.2%

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1316
Missing (%)98.5%
Memory size10.6 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1318
Missing (%)98.7%
Memory size10.6 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1318
Missing (%)98.7%
Memory size10.6 KiB

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1314
Missing (%)98.4%
Memory size10.6 KiB

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1313
Missing (%)98.3%
Memory size10.6 KiB

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1336
Missing (%)100.0%
Memory size11.9 KiB

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1336
Missing (%)100.0%
Memory size11.9 KiB

Unnamed: 14
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing1334
Missing (%)99.9%
Memory size10.6 KiB
2024-03-14T22:31:08.920115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters6
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

Unique2 ?
Unique (%)100.0%

Sample

1st row칠엽수
2nd row소나무
ValueCountFrequency (%)
칠엽수 1
50.0%
소나무 1
50.0%
2024-03-14T22:31:09.560344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
칠 1
16.7%
엽 1
16.7%
수 1
16.7%
소 1
16.7%
나 1
16.7%
무 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
칠 1
16.7%
엽 1
16.7%
수 1
16.7%
소 1
16.7%
나 1
16.7%
무 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
칠 1
16.7%
엽 1
16.7%
수 1
16.7%
소 1
16.7%
나 1
16.7%
무 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
칠 1
16.7%
엽 1
16.7%
수 1
16.7%
소 1
16.7%
나 1
16.7%
무 1
16.7%

Unnamed: 15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1308
Missing (%)97.9%
Memory size10.6 KiB

Unnamed: 16
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1310
Missing (%)98.1%
Memory size10.6 KiB

Unnamed: 17
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1310
Missing (%)98.1%
Memory size10.6 KiB

Unnamed: 18
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1308
Missing (%)97.9%
Memory size10.6 KiB

Unnamed: 19
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1308
Missing (%)97.9%
Memory size10.6 KiB

Interactions

2024-03-14T22:31:01.858278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:31:01.302345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:31:02.136238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:31:01.579001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:31:09.744412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
no수종흉고직경(DBH)Unnamed: 6Unnamed: 14
no1.0000.9710.852NaNNaN
수종0.9711.0000.547NaNNaN
흉고직경(DBH)0.8520.5471.0001.0000.000
Unnamed: 6NaNNaN1.0001.000NaN
Unnamed: 14NaNNaN0.000NaN1.000
2024-03-14T22:31:10.015105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
no흉고직경(DBH)수종
no1.000-0.2380.913
흉고직경(DBH)-0.2381.0000.383
수종0.9130.3831.000

Missing values

2024-03-14T22:31:02.554938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:31:03.284625image/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.
2024-03-14T22:31:03.807193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

no수종흉고직경(DBH)Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
01이팝나무13.7<NA><NA><NA>이팝나무DBH(cm)본수탄소저장량(kg C)산정탄소흡수량 ton CO2<NA><NA>칠엽수DBH(cm)본수탄소저장량(kg C)산정탄소흡수량 ton CO2
12이팝나무13.2<NA><NA><NA><NA>14119191.118986<NA><NA><NA>16214.328.61.212051
23이팝나무13.1<NA><NA><NA><NA>124313.6584.844.161826<NA><NA><NA>141710.7181.99.841504
34이팝나무13.0<NA><NA><NA><NA>10899.2818.891.404709<NA><NA><NA>12917.6691.652.680992
45이팝나무12.8<NA><NA><NA><NA>835.717.12.80296<NA><NA><NA>10585.1295.831.791795
56이팝나무12.7<NA><NA><NA><NA>6183.155.815.135984<NA><NA><NA>843.212.82.192538
67이팝나무12.7<NA><NA><NA><NA>합계NaNNaN1495.5154.624464<NA><NA><NA>합계NaNNaN1210.797.71888
78이팝나무12.5<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
89이팝나무12.4<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
910이팝나무12.3<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA>소나무DBH(cm)본수탄소저장량(kg C)산정탄소흡수량 ton CO2
no수종흉고직경(DBH)Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
13261327소나무6.1<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13271328소나무6.1<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13281329소나무6.1<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13291330소나무6.1<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13301331소나무6.0<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13311332소나무5.9<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13321333소나무5.8<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13331334소나무5.8<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13341335소나무5.5<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN
13351336소나무5.5<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA>NaNNaNNaNNaNNaN