Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory53.3 B

Variable types

Numeric4
Text1
Categorical1

Alerts

순번 is highly overall correlated with 측정시각High correlation
측정시각 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 06:13:41.862444
Analysis finished2023-12-10 06:13:44.940286
Duration3.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  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
2023-12-10T15:13:45.055313image/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
2023-12-10T15:13:45.269721image/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%

택시아이디
Text

Distinct55
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T15:13:45.815843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1000
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st rowT_99659190
2nd rowT_47278771
3rd rowT_22187217
4th rowT_48743645
5th rowT_96070250
ValueCountFrequency (%)
t_47132284 3
 
3.0%
t_50647980 2
 
2.0%
t_47278771 2
 
2.0%
t_26215619 2
 
2.0%
t_99659190 2
 
2.0%
t_23432359 2
 
2.0%
t_26874812 2
 
2.0%
t_47352015 2
 
2.0%
t_74421149 2
 
2.0%
t_25043720 2
 
2.0%
Other values (45) 79
79.0%
2023-12-10T15:13:46.383047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 113
11.3%
7 112
11.2%
T 100
10.0%
_ 100
10.0%
4 92
9.2%
8 81
8.1%
9 76
7.6%
0 71
7.1%
3 70
7.0%
1 69
6.9%
Other values (2) 116
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 800
80.0%
Uppercase Letter 100
 
10.0%
Connector Punctuation 100
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 113
14.1%
7 112
14.0%
4 92
11.5%
8 81
10.1%
9 76
9.5%
0 71
8.9%
3 70
8.8%
1 69
8.6%
6 58
7.2%
5 58
7.2%
Uppercase Letter
ValueCountFrequency (%)
T 100
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 900
90.0%
Latin 100
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 113
12.6%
7 112
12.4%
_ 100
11.1%
4 92
10.2%
8 81
9.0%
9 76
8.4%
0 71
7.9%
3 70
7.8%
1 69
7.7%
6 58
6.4%
Latin
ValueCountFrequency (%)
T 100
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 113
11.3%
7 112
11.2%
T 100
10.0%
_ 100
10.0%
4 92
9.2%
8 81
8.1%
9 76
7.6%
0 71
7.1%
3 70
7.0%
1 69
6.9%
Other values (2) 116
11.6%

위도값
Real number (ℝ)

Distinct88
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.530552
Minimum37.39786
Maximum37.67343
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:13:46.586831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.39786
5-th percentile37.466428
Q137.490243
median37.52096
Q337.565876
95-th percentile37.652744
Maximum37.67343
Range0.27557
Interquartile range (IQR)0.07563275

Descriptive statistics

Standard deviation0.056678565
Coefficient of variation (CV)0.001510198
Kurtosis0.20921212
Mean37.530552
Median Absolute Deviation (MAD)0.0375465
Skewness0.43028274
Sum3753.0552
Variance0.0032124597
MonotonicityNot monotonic
2023-12-10T15:13:46.886976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.52096 2
 
2.0%
37.39786 2
 
2.0%
37.594215 2
 
2.0%
37.434925 2
 
2.0%
37.482277 2
 
2.0%
37.55336 2
 
2.0%
37.565876 2
 
2.0%
37.522633 2
 
2.0%
37.659283 2
 
2.0%
37.67343 2
 
2.0%
Other values (78) 80
80.0%
ValueCountFrequency (%)
37.39786 2
2.0%
37.43064 1
1.0%
37.434925 2
2.0%
37.468086 1
1.0%
37.469578 1
1.0%
37.469692 1
1.0%
37.471317 1
1.0%
37.471348 1
1.0%
37.48054 1
1.0%
37.48061 1
1.0%
ValueCountFrequency (%)
37.67343 2
2.0%
37.659283 2
2.0%
37.652752 1
1.0%
37.652744 1
1.0%
37.61152 1
1.0%
37.6114 1
1.0%
37.605473 1
1.0%
37.605343 1
1.0%
37.599487 1
1.0%
37.594585 1
1.0%

경도값
Real number (ℝ)

Distinct78
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98554
Minimum126.65185
Maximum127.25926
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:13:47.097494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.65185
5-th percentile126.76685
Q1126.95217
median127.01036
Q3127.04147
95-th percentile127.10299
Maximum127.25926
Range0.607405
Interquartile range (IQR)0.0893

Descriptive statistics

Standard deviation0.099695622
Coefficient of variation (CV)0.00078509431
Kurtosis2.1874198
Mean126.98554
Median Absolute Deviation (MAD)0.0472565
Skewness-1.0354575
Sum12698.554
Variance0.0099392171
MonotonicityNot monotonic
2023-12-10T15:13:47.309809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.98782 3
 
3.0%
127.01797 2
 
2.0%
127.05532 2
 
2.0%
127.01416 2
 
2.0%
126.9207 2
 
2.0%
127.024155 2
 
2.0%
126.766846 2
 
2.0%
126.905 2
 
2.0%
127.07274 2
 
2.0%
126.753555 2
 
2.0%
Other values (68) 79
79.0%
ValueCountFrequency (%)
126.651855 2
2.0%
126.753555 2
2.0%
126.766846 2
2.0%
126.792534 2
2.0%
126.836586 2
2.0%
126.88755 1
1.0%
126.887596 1
1.0%
126.89137 1
1.0%
126.89152 1
1.0%
126.89854 2
2.0%
ValueCountFrequency (%)
127.25926 1
1.0%
127.15487 1
1.0%
127.15483 1
1.0%
127.10418 1
1.0%
127.10415 1
1.0%
127.10293 1
1.0%
127.1028 1
1.0%
127.0897 2
2.0%
127.088524 1
1.0%
127.0862 2
2.0%

온도감지기값
Real number (ℝ)

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.34820325
Minimum-4.581903
Maximum7.979324
Zeros0
Zeros (%)0.0%
Negative56
Negative (%)56.0%
Memory size1.0 KiB
2023-12-10T15:13:47.559300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4.581903
5-th percentile-4.341573
Q1-1.3921953
median-0.17052
Q30.58585125
95-th percentile3.191424
Maximum7.979324
Range12.561227
Interquartile range (IQR)1.9780465

Descriptive statistics

Standard deviation2.3850072
Coefficient of variation (CV)-6.8494685
Kurtosis1.9209761
Mean-0.34820325
Median Absolute Deviation (MAD)0.915923
Skewness0.59474172
Sum-34.820325
Variance5.6882593
MonotonicityNot monotonic
2023-12-10T15:13:47.783700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.215915 3
 
3.0%
-0.453574 2
 
2.0%
-1.524376 2
 
2.0%
-0.838102 2
 
2.0%
1.231403 2
 
2.0%
-0.942245 2
 
2.0%
2.465095 2
 
2.0%
-0.547036 2
 
2.0%
0.547799 2
 
2.0%
-4.341573 2
 
2.0%
Other values (53) 79
79.0%
ValueCountFrequency (%)
-4.581903 2
2.0%
-4.47509 2
2.0%
-4.341573 2
2.0%
-4.240101 2
2.0%
-4.119936 2
2.0%
-3.933013 2
2.0%
-3.471046 2
2.0%
-2.955672 1
1.0%
-2.942321 1
1.0%
-2.840848 2
2.0%
ValueCountFrequency (%)
7.979324 2
2.0%
4.622721 2
2.0%
3.191424 2
2.0%
3.167391 2
2.0%
2.465095 2
2.0%
2.131304 1
1.0%
2.037842 2
2.0%
1.316854 1
1.0%
1.303502 1
1.0%
1.231403 2
2.0%

측정시각
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2021-01-01 00:00:00
56 
2021-01-01 00:00:01
44 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-01 00:00:00
2nd row2021-01-01 00:00:00
3rd row2021-01-01 00:00:00
4th row2021-01-01 00:00:00
5th row2021-01-01 00:00:00

Common Values

ValueCountFrequency (%)
2021-01-01 00:00:00 56
56.0%
2021-01-01 00:00:01 44
44.0%

Length

2023-12-10T15:13:47.955771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:13:48.077779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-01 100
50.0%
00:00:00 56
28.0%
00:00:01 44
22.0%

Interactions

2023-12-10T15:13:43.909317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:42.135353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:42.737740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:43.325378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:44.044541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:42.348293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:42.864155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:43.465975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:44.194763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:42.497711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:43.029075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:43.610020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:44.379117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:42.605465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:43.169769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:43.766211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:13:48.165854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번택시아이디위도값경도값온도감지기값측정시각
순번1.0000.0000.2510.2780.2080.996
택시아이디0.0001.0001.0001.0001.0000.000
위도값0.2511.0001.0000.7850.7890.000
경도값0.2781.0000.7851.0000.7130.000
온도감지기값0.2081.0000.7890.7131.0000.000
측정시각0.9960.0000.0000.0000.0001.000
2023-12-10T15:13:48.324697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도값경도값온도감지기값측정시각
순번1.000-0.024-0.028-0.0910.906
위도값-0.0241.0000.037-0.2130.000
경도값-0.0280.0371.000-0.0730.000
온도감지기값-0.091-0.213-0.0731.0000.000
측정시각0.9060.0000.0000.0001.000

Missing values

2023-12-10T15:13:44.669997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:13:44.863020image/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

순번택시아이디위도값경도값온도감지기값측정시각
01T_9965919037.52096127.017971.3035022021-01-01 00:00:00
12T_4727877137.6114127.07274-4.5819032021-01-01 00:00:00
23T_2218721737.562202127.065090.7534142021-01-01 00:00:00
34T_4874364537.54574126.836586-4.2401012021-01-01 00:00:00
45T_9607025037.55994127.15483-3.4710462021-01-01 00:00:00
56T_9797458637.546444126.8875963.1673912021-01-01 00:00:00
67T_7222383837.487724126.982472.1313042021-01-01 00:00:00
78T_9921972837.536297126.9631650.2460522021-01-01 00:00:00
89T_2108856237.489605126.891520.3635462021-01-01 00:00:00
910T_2475074637.57153127.009447.9793242021-01-01 00:00:00
순번택시아이디위도값경도값온도감지기값측정시각
9091T_5064798037.522633126.920616-0.5470362021-01-01 00:00:01
9192T_9760836737.48327127.024763.1914242021-01-01 00:00:01
9293T_4727877137.61152127.07274-4.5819032021-01-01 00:00:01
9394T_7229708237.605473127.04719-4.3415732021-01-01 00:00:01
9495T_9607025037.559963127.15487-3.4710462021-01-01 00:00:01
9596T_9753512437.594215127.08622.4650952021-01-01 00:00:01
9697T_4874364537.545742126.836586-4.2401012021-01-01 00:00:01
9798T_4713228437.56588126.98782-0.2159152021-01-01 00:00:01
9899T_7464087937.4938127.01416-2.8408482021-01-01 00:00:01
99100T_2357884737.39786126.6518552.0378422021-01-01 00:00:01