Overview

Dataset statistics

Number of variables8
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory73.0 B

Variable types

Text1
Categorical2
Numeric5

Dataset

Description국가광물자원지리정보망(KMRGIS)에 업데이트된 광산별 기술보고서, 매장량보고서, 시추보고서 등을 리스트업
URLhttps://www.data.go.kr/data/3074446/fileData.do

Alerts

광산수 is highly overall correlated with 광량(확정) and 3 other fieldsHigh correlation
광량(확정) is highly overall correlated with 광산수 and 2 other fieldsHigh correlation
광량(추정) is highly overall correlated with 광산수 and 2 other fieldsHigh correlation
광량(계) is highly overall correlated with 광산수 and 3 other fieldsHigh correlation
가채광량 is highly overall correlated with 광산수 and 3 other fieldsHigh correlation
단위 is highly imbalanced (75.4%)Imbalance
광종 has unique valuesUnique
광량(추정) has unique valuesUnique
광량(계) has unique valuesUnique
가채광량 has unique valuesUnique
광량(확정) has 11 (33.3%) zerosZeros

Reproduction

Analysis started2023-12-12 12:06:24.949242
Analysis finished2023-12-12 12:06:28.895842
Duration3.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

광종
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T21:06:29.063329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
Distinct characters53
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

Unique33 ?
Unique (%)100.0%

Sample

1st row
2nd row
3rd row
4th row연_아연
5th row
ValueCountFrequency (%)
1
 
3.0%
운모 1
 
3.0%
석탄광 1
 
3.0%
연옥 1
 
3.0%
규사 1
 
3.0%
홍주석 1
 
3.0%
중정석 1
 
3.0%
수정 1
 
3.0%
사문석 1
 
3.0%
명반석 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T21:06:29.469767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
18.3%
4
 
4.9%
4
 
4.9%
3
 
3.7%
3
 
3.7%
2
 
2.4%
2
 
2.4%
2
 
2.4%
2
 
2.4%
2
 
2.4%
Other values (43) 43
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81
98.8%
Connector Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
18.5%
4
 
4.9%
4
 
4.9%
3
 
3.7%
3
 
3.7%
2
 
2.5%
2
 
2.5%
2
 
2.5%
2
 
2.5%
2
 
2.5%
Other values (42) 42
51.9%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81
98.8%
Common 1
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
 
18.5%
4
 
4.9%
4
 
4.9%
3
 
3.7%
3
 
3.7%
2
 
2.5%
2
 
2.5%
2
 
2.5%
2
 
2.5%
2
 
2.5%
Other values (42) 42
51.9%
Common
ValueCountFrequency (%)
_ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81
98.8%
ASCII 1
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
15
 
18.5%
4
 
4.9%
4
 
4.9%
3
 
3.7%
3
 
3.7%
2
 
2.5%
2
 
2.5%
2
 
2.5%
2
 
2.5%
2
 
2.5%
Other values (42) 42
51.9%
ASCII
ValueCountFrequency (%)
_ 1
100.0%

단위
Categorical

IMBALANCE 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
천톤
31 
kg
 
1
 
1

Length

Max length2
Median length2
Mean length1.969697
Min length1

Unique

Unique2 ?
Unique (%)6.1%

Sample

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

Common Values

ValueCountFrequency (%)
천톤 31
93.9%
kg 1
 
3.0%
1
 
3.0%

Length

2023-12-12T21:06:29.648989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:06:29.788338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천톤 31
93.9%
kg 1
 
3.0%
1
 
3.0%

광산수
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.333333
Minimum1
Maximum265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T21:06:29.931603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median14
Q331
95-th percentile225.2
Maximum265
Range264
Interquartile range (IQR)27

Descriptive statistics

Standard deviation70.114935
Coefficient of variation (CV)1.7383868
Kurtosis4.8413303
Mean40.333333
Median Absolute Deviation (MAD)12
Skewness2.4001293
Sum1331
Variance4916.1042
MonotonicityNot monotonic
2023-12-12T21:06:30.086713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 5
 
15.2%
14 3
 
9.1%
5 2
 
6.1%
2 2
 
6.1%
95 1
 
3.0%
11 1
 
3.0%
19 1
 
3.0%
214 1
 
3.0%
3 1
 
3.0%
6 1
 
3.0%
Other values (15) 15
45.5%
ValueCountFrequency (%)
1 5
15.2%
2 2
 
6.1%
3 1
 
3.0%
4 1
 
3.0%
5 2
 
6.1%
6 1
 
3.0%
7 1
 
3.0%
9 1
 
3.0%
11 1
 
3.0%
13 1
 
3.0%
ValueCountFrequency (%)
265 1
3.0%
242 1
3.0%
214 1
3.0%
132 1
3.0%
95 1
3.0%
50 1
3.0%
38 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%

품위
Categorical

Distinct15
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Memory size396.0 B
각급
19 
Au 7.8g/t
 
1
Ag 195.2g/t
 
1
Cu 2.1%
 
1
Pb 2.4%_Zn 2.7%
 
1
Other values (10)
10 

Length

Max length15
Median length2
Mean length4.8787879
Min length2

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st rowAu 7.8g/t
2nd rowAg 195.2g/t
3rd rowCu 2.1%
4th rowPb 2.4%_Zn 2.7%
5th rowFe 40.0%

Common Values

ValueCountFrequency (%)
각급 19
57.6%
Au 7.8g/t 1
 
3.0%
Ag 195.2g/t 1
 
3.0%
Cu 2.1% 1
 
3.0%
Pb 2.4%_Zn 2.7% 1
 
3.0%
Fe 40.0% 1
 
3.0%
WO₃ 0.5% 1
 
3.0%
MoS₂ 0.3% 1
 
3.0%
Mn 19.6% 1
 
3.0%
Sb 2.1% 1
 
3.0%
Other values (5) 5
 
15.2%

Length

2023-12-12T21:06:30.248121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
각급 19
40.4%
2.1 3
 
6.4%
au 2
 
4.3%
mos₂ 1
 
2.1%
u₃o8 1
 
2.1%
na 1
 
2.1%
r₂o₃ 1
 
2.1%
0.9g/m² 1
 
2.1%
1.9 1
 
2.1%
sn 1
 
2.1%
Other values (16) 16
34.0%

광량(확정)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61025.842
Minimum0
Maximum1751998.2
Zeros11
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T21:06:30.378053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median104
Q33165
95-th percentile87725.5
Maximum1751998.2
Range1751998.2
Interquartile range (IQR)3165

Descriptive statistics

Standard deviation305181.98
Coefficient of variation (CV)5.0008647
Kurtosis32.235454
Mean61025.842
Median Absolute Deviation (MAD)104
Skewness5.6535654
Sum2013852.8
Variance9.3136042 × 1010
MonotonicityNot monotonic
2023-12-12T21:06:30.501475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 11
33.3%
1894.8 1
 
3.0%
7882.4 1
 
3.0%
25652.5 1
 
3.0%
180835.0 1
 
3.0%
17.6 1
 
3.0%
611.1 1
 
3.0%
53.0 1
 
3.0%
104.0 1
 
3.0%
1941.1 1
 
3.0%
Other values (13) 13
39.4%
ValueCountFrequency (%)
0.0 11
33.3%
10.0 1
 
3.0%
10.4 1
 
3.0%
13.0 1
 
3.0%
17.6 1
 
3.0%
53.0 1
 
3.0%
104.0 1
 
3.0%
258.3 1
 
3.0%
611.1 1
 
3.0%
1274.2 1
 
3.0%
ValueCountFrequency (%)
1751998.2 1
3.0%
180835.0 1
3.0%
25652.5 1
3.0%
10454.5 1
3.0%
10004.0 1
3.0%
7882.4 1
3.0%
7818.6 1
3.0%
5711.3 1
3.0%
3165.0 1
3.0%
2249.3 1
3.0%

광량(추정)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean479892.03
Minimum12
Maximum12055876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T21:06:30.637050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile68.4
Q12061.1
median6173.3
Q329284.4
95-th percentile1303854.8
Maximum12055876
Range12055864
Interquartile range (IQR)27223.3

Descriptive statistics

Standard deviation2139006.3
Coefficient of variation (CV)4.4572657
Kurtosis29.103877
Mean479892.03
Median Absolute Deviation (MAD)5942.3
Skewness5.31235
Sum15836437
Variance4.575348 × 1012
MonotonicityNot monotonic
2023-12-12T21:06:30.780160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4026.9 1
 
3.0%
22456.1 1
 
3.0%
2491.5 1
 
3.0%
424.0 1
 
3.0%
16612.5 1
 
3.0%
3198.0 1
 
3.0%
4234.5 1
 
3.0%
29284.4 1
 
3.0%
44.4 1
 
3.0%
4573.4 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
12.0 1
3.0%
44.4 1
3.0%
84.4 1
3.0%
231.0 1
3.0%
360.0 1
3.0%
423.0 1
3.0%
424.0 1
3.0%
1041.0 1
3.0%
2061.1 1
3.0%
2491.5 1
3.0%
ValueCountFrequency (%)
12055875.8 1
3.0%
2924902.8 1
3.0%
223156.1 1
3.0%
185697.0 1
3.0%
112233.6 1
3.0%
95474.3 1
3.0%
47931.6 1
3.0%
31194.6 1
3.0%
29284.4 1
3.0%
22456.1 1
3.0%

광량(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean569870.72
Minimum22
Maximum13807874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T21:06:30.908943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile78.96
Q12319.4
median7738.3
Q329284.4
95-th percentile1966299.7
Maximum13807874
Range13807852
Interquartile range (IQR)26965

Descriptive statistics

Standard deviation2439083.5
Coefficient of variation (CV)4.2800647
Kurtosis29.447965
Mean569870.72
Median Absolute Deviation (MAD)7634.7
Skewness5.3383672
Sum18805734
Variance5.9491285 × 1012
MonotonicityNot monotonic
2023-12-12T21:06:31.045346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
5921.7 1
 
3.0%
22456.1 1
 
3.0%
2595.5 1
 
3.0%
477.0 1
 
3.0%
16612.5 1
 
3.0%
3198.0 1
 
3.0%
4234.5 1
 
3.0%
29284.4 1
 
3.0%
44.4 1
 
3.0%
7738.3 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
22.0 1
3.0%
44.4 1
3.0%
102.0 1
3.0%
360.0 1
3.0%
436.0 1
3.0%
477.0 1
3.0%
842.1 1
3.0%
1041.0 1
3.0%
2319.4 1
3.0%
2595.5 1
3.0%
ValueCountFrequency (%)
13807874.0 1
3.0%
2932785.2 1
3.0%
1321976.0 1
3.0%
223166.5 1
3.0%
113507.8 1
3.0%
97723.6 1
3.0%
73584.1 1
3.0%
41649.0 1
3.0%
29284.4 1
3.0%
25972.0 1
3.0%

가채광량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean415744
Minimum17.4
Maximum10709107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T21:06:31.194594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.4
5-th percentile57.38
Q11675.3
median6050.1
Q321543.4
95-th percentile1038986.4
Maximum10709107
Range10709090
Interquartile range (IQR)19868.1

Descriptive statistics

Standard deviation1885007.2
Coefficient of variation (CV)4.5340575
Kurtosis30.248042
Mean415744
Median Absolute Deviation (MAD)5742.6
Skewness5.4326376
Sum13719552
Variance3.5532521 × 1012
MonotonicityNot monotonic
2023-12-12T21:06:31.381435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4523.5 1
 
3.0%
17682.0 1
 
3.0%
1837.6 1
 
3.0%
344.5 1
 
3.0%
11630.1 1
 
3.0%
2266.4 1
 
3.0%
3069.0 1
 
3.0%
21543.4 1
 
3.0%
31.1 1
 
3.0%
6050.1 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
17.4 1
3.0%
31.1 1
3.0%
74.9 1
3.0%
252.0 1
3.0%
307.5 1
3.0%
344.5 1
3.0%
711.7 1
3.0%
728.7 1
3.0%
1675.3 1
3.0%
1837.6 1
3.0%
ValueCountFrequency (%)
10709107.1 1
3.0%
2140117.4 1
3.0%
304899.0 1
3.0%
178059.4 1
3.0%
82283.9 1
3.0%
74811.8 1
3.0%
53998.6 1
3.0%
31244.7 1
3.0%
21543.4 1
3.0%
20181.2 1
3.0%

Interactions

2023-12-12T21:06:27.970923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:25.316649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:26.217396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:26.775909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:27.364823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:28.099313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:25.436156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:26.332709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:26.875426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:27.492928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:28.227182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:25.894399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:26.448640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:27.019272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:27.617356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:28.344545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:26.015449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:26.562540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:06:27.158075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/