Overview

Dataset statistics

Number of variables16
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.8 KiB
Average record size in memory141.3 B

Variable types

Numeric9
Categorical4
Text3

Alerts

도로종류 has constant value ""Constant
측정일 has constant value ""Constant
측정시간 has constant value ""Constant
co is highly overall correlated with nox and 3 other fieldsHigh correlation
nox is highly overall correlated with co and 3 other fieldsHigh correlation
hc is highly overall correlated with co and 3 other fieldsHigh correlation
pm is highly overall correlated with co and 3 other fieldsHigh correlation
co2 is highly overall correlated with co and 3 other fieldsHigh correlation
기본키 has unique valuesUnique
co has unique valuesUnique
nox has unique valuesUnique
pm has unique valuesUnique
co2 has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:32:29.282955
Analysis finished2023-12-10 10:32:47.967667
Duration18.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:48.190312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T19:32:48.563638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

도로종류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
건기연
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건기연 100
100.0%

Length

2023-12-10T19:32:48.826010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:32:48.986155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건기연 100
100.0%

지점
Text

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:32:49.532080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.04
Min length8

Characters and Unicode

Total characters804
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[0114-1]
2nd row[0114-1]
3rd row[0115-1]
4th row[0115-1]
5th row[0116-2]
ValueCountFrequency (%)
0114-1 2
 
2.0%
2609-1 2
 
2.0%
3005-3 2
 
2.0%
2313-2 2
 
2.0%
2316-0 2
 
2.0%
2317-0 2
 
2.0%
2320-2 2
 
2.0%
2602-3 2
 
2.0%
2602-4 2
 
2.0%
2605-0 2
 
2.0%
Other values (40) 80
80.0%
2023-12-10T19:32:50.457726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 136
16.9%
0 104
12.9%
2 104
12.9%
[ 100
12.4%
- 100
12.4%
] 100
12.4%
3 44
 
5.5%
7 34
 
4.2%
9 26
 
3.2%
6 24
 
3.0%
Other values (3) 32
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 504
62.7%
Open Punctuation 100
 
12.4%
Dash Punctuation 100
 
12.4%
Close Punctuation 100
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 136
27.0%
0 104
20.6%
2 104
20.6%
3 44
 
8.7%
7 34
 
6.7%
9 26
 
5.2%
6 24
 
4.8%
5 14
 
2.8%
4 12
 
2.4%
8 6
 
1.2%
Open Punctuation
ValueCountFrequency (%)
[ 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Close Punctuation
ValueCountFrequency (%)
] 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 136
16.9%
0 104
12.9%
2 104
12.9%
[ 100
12.4%
- 100
12.4%
] 100
12.4%
3 44
 
5.5%
7 34
 
4.2%
9 26
 
3.2%
6 24
 
3.0%
Other values (3) 32
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 136
16.9%
0 104
12.9%
2 104
12.9%
[ 100
12.4%
- 100
12.4%
] 100
12.4%
3 44
 
5.5%
7 34
 
4.2%
9 26
 
3.2%
6 24
 
3.0%
Other values (3) 32
 
4.0%

방향
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
50 
2
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 50
50.0%
2 50
50.0%

Length

2023-12-10T19:32:50.810452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:32:51.009126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 50
50.0%
2 50
50.0%
Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:32:51.510504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.14
Min length5

Characters and Unicode

Total characters514
Distinct characters82
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row태인-금구
2nd row태인-금구
3rd row정읍-태인
4th row정읍-태인
5th row금산-전주
ValueCountFrequency (%)
태인-금구 2
 
2.0%
천천-장계 2
 
2.0%
부안ic-화호 2
 
2.0%
고창-흥덕 2
 
2.0%
보안-부안 2
 
2.0%
부안-죽산 2
 
2.0%
군산-익산 2
 
2.0%
군산-대야 2
 
2.0%
군산-전주 2
 
2.0%
공덕-완주 2
 
2.0%
Other values (40) 80
80.0%
2023-12-10T19:32:52.244593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 100
 
19.5%
22
 
4.3%
22
 
4.3%
16
 
3.1%
14
 
2.7%
12
 
2.3%
12
 
2.3%
10
 
1.9%
10
 
1.9%
10
 
1.9%
Other values (72) 286
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 406
79.0%
Dash Punctuation 100
 
19.5%
Uppercase Letter 8
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
22
 
5.4%
22
 
5.4%
16
 
3.9%
14
 
3.4%
12
 
3.0%
12
 
3.0%
10
 
2.5%
10
 
2.5%
10
 
2.5%
10
 
2.5%
Other values (69) 268
66.0%
Uppercase Letter
ValueCountFrequency (%)
C 4
50.0%
I 4
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 406
79.0%
Common 100
 
19.5%
Latin 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
22
 
5.4%
22
 
5.4%
16
 
3.9%
14
 
3.4%
12
 
3.0%
12
 
3.0%
10
 
2.5%
10
 
2.5%
10
 
2.5%
10
 
2.5%
Other values (69) 268
66.0%
Latin
ValueCountFrequency (%)
C 4
50.0%
I 4
50.0%
Common
ValueCountFrequency (%)
- 100
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 406
79.0%
ASCII 108
 
21.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 100
92.6%
C 4
 
3.7%
I 4
 
3.7%
Hangul
ValueCountFrequency (%)
22
 
5.4%
22
 
5.4%
16
 
3.9%
14
 
3.4%
12
 
3.0%
12
 
3.0%
10
 
2.5%
10
 
2.5%
10
 
2.5%
10
 
2.5%
Other values (69) 268
66.0%

연장
Real number (ℝ)

Distinct42
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.122
Minimum0.9
Maximum18.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:52.546760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile2.4
Q14.3
median6.15
Q38.7
95-th percentile14.6
Maximum18.9
Range18
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation4.0080369
Coefficient of variation (CV)0.56276845
Kurtosis0.63460065
Mean7.122
Median Absolute Deviation (MAD)2.45
Skewness0.94936942
Sum712.2
Variance16.06436
MonotonicityNot monotonic
2023-12-10T19:32:52.832026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
6.0 4
 
4.0%
3.2 4
 
4.0%
4.9 4
 
4.0%
2.4 4
 
4.0%
6.5 4
 
4.0%
5.4 4
 
4.0%
8.0 4
 
4.0%
8.7 4
 
4.0%
6.3 2
 
2.0%
7.5 2
 
2.0%
Other values (32) 64
64.0%
ValueCountFrequency (%)
0.9 2
2.0%
1.0 2
2.0%
2.4 4
4.0%
2.7 2
2.0%
3.2 4
4.0%
3.3 2
2.0%
3.4 2
2.0%
3.6 2
2.0%
3.7 2
2.0%
4.1 2
2.0%
ValueCountFrequency (%)
18.9 2
2.0%
17.3 2
2.0%
14.6 2
2.0%
13.8 2
2.0%
13.0 2
2.0%
12.9 2
2.0%
11.9 2
2.0%
11.7 2
2.0%
11.5 2
2.0%
11.1 2
2.0%

측정일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210101
2nd row20210101
3rd row20210101
4th row20210101
5th row20210101

Common Values

ValueCountFrequency (%)
20210101 100
100.0%

Length

2023-12-10T19:32:53.159721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:32:53.481296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210101 100
100.0%

측정시간
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:32:53.754143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:32:53.936038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

좌표위치위도
Real number (ℝ)

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.698112
Minimum35.31836
Maximum36.05245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:54.325352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.31836
5-th percentile35.38415
Q135.52961
median35.72265
Q335.87978
95-th percentile35.97701
Maximum36.05245
Range0.73409
Interquartile range (IQR)0.35017

Descriptive statistics

Standard deviation0.194329
Coefficient of variation (CV)0.0054436772
Kurtosis-1.0353721
Mean35.698112
Median Absolute Deviation (MAD)0.16868
Skewness-0.16909629
Sum3569.8112
Variance0.037763758
MonotonicityNot monotonic
2023-12-10T19:32:54.683437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.66929 2
 
2.0%
35.71626 2
 
2.0%
35.69967 2
 
2.0%
35.75539 2
 
2.0%
35.97701 2
 
2.0%
35.9615 2
 
2.0%
35.9389 2
 
2.0%
35.87978 2
 
2.0%
35.85422 2
 
2.0%
35.77224 2
 
2.0%
Other values (40) 80
80.0%
ValueCountFrequency (%)
35.31836 2
2.0%
35.36379 2
2.0%
35.38415 2
2.0%
35.40351 2
2.0%
35.41493 2
2.0%
35.42787 2
2.0%
35.44376 2
2.0%
35.44964 2
2.0%
35.467 2
2.0%
35.48235 2
2.0%
ValueCountFrequency (%)
36.05245 2
2.0%
35.97732 2
2.0%
35.97701 2
2.0%
35.97553 2
2.0%
35.9615 2
2.0%
35.9389 2
2.0%
35.9258 2
2.0%
35.91702 2
2.0%
35.91078 2
2.0%
35.9058 2
2.0%

좌표위치경도
Real number (ℝ)

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.09958
Minimum126.5004
Maximum127.67801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:55.075070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5004
5-th percentile126.64598
Q1126.88133
median127.06941
Q3127.31509
95-th percentile127.59682
Maximum127.67801
Range1.17761
Interquartile range (IQR)0.43376

Descriptive statistics

Standard deviation0.29977612
Coefficient of variation (CV)0.0023585925
Kurtosis-0.79550916
Mean127.09958
Median Absolute Deviation (MAD)0.215435
Skewness0.20628666
Sum12709.958
Variance0.089865724
MonotonicityNot monotonic
2023-12-10T19:32:55.579671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.96828 2
 
2.0%
127.11512 2
 
2.0%
126.69676 2
 
2.0%
126.75919 2
 
2.0%
126.91023 2
 
2.0%
126.77112 2
 
2.0%
126.84434 2
 
2.0%
126.98112 2
 
2.0%
127.21711 2
 
2.0%
127.4985 2
 
2.0%
Other values (40) 80
80.0%
ValueCountFrequency (%)
126.5004 2
2.0%
126.59317 2
2.0%
126.64598 2
2.0%
126.69676 2
2.0%
126.6981 2
2.0%
126.75919 2
2.0%
126.77112 2
2.0%
126.77892 2
2.0%
126.7879 2
2.0%
126.83701 2
2.0%
ValueCountFrequency (%)
127.67801 2
2.0%
127.65033 2
2.0%
127.59682 2
2.0%
127.57067 2
2.0%
127.55201 2
2.0%
127.53885 2
2.0%
127.53076 2
2.0%
127.52057 2
2.0%
127.4985 2
2.0%
127.42317 2
2.0%

co
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2577.4416
Minimum36.23
Maximum13695.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:56.102233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.23
5-th percentile122.0835
Q1651.0375
median1805.02
Q34131.99
95-th percentile7337.279
Maximum13695.22
Range13658.99
Interquartile range (IQR)3480.9525

Descriptive statistics

Standard deviation2580.0681
Coefficient of variation (CV)1.001019
Kurtosis5.2722839
Mean2577.4416
Median Absolute Deviation (MAD)1336.655
Skewness1.9368154
Sum257744.16
Variance6656751.6
MonotonicityNot monotonic
2023-12-10T19:32:56.403449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/