Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells62652
Missing cells (%)24.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory233.0 B

Variable types

Numeric10
Categorical7
DateTime2
Unsupported5
Text2

Alerts

card_at is highly imbalanced (56.8%)Imbalance
bssh_no has 1103 (11.0%) missing valuesMissing
gugun_cd has 1106 (11.1%) missing valuesMissing
prices has 10000 (100.0%) missing valuesMissing
rm has 9340 (93.4%) missing valuesMissing
bssh_nm has 10000 (100.0%) missing valuesMissing
la has 10000 (100.0%) missing valuesMissing
lo has 10000 (100.0%) missing valuesMissing
adres has 10000 (100.0%) missing valuesMissing
telno has 1103 (11.0%) missing valuesMissing
skey has unique valuesUnique
prices is an unsupported type, check if it needs cleaning or further analysisUnsupported
bssh_nm is an unsupported type, check if it needs cleaning or further analysisUnsupported
la is an unsupported type, check if it needs cleaning or further analysisUnsupported
lo is an unsupported type, check if it needs cleaning or further analysisUnsupported
adres is an unsupported type, check if it needs cleaning or further analysisUnsupported
unitprice has 588 (5.9%) zerosZeros

Reproduction

Analysis started2024-04-17 10:03:13.213461
Analysis finished2024-04-17 10:03:13.770106
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83418.821
Minimum47955
Maximum118536
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:13.831083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47955
5-th percentile51525.9
Q165886.5
median83389
Q3100969
95-th percentile115032.35
Maximum118536
Range70581
Interquartile range (IQR)35082.5

Descriptive statistics

Standard deviation20314.119
Coefficient of variation (CV)0.24351962
Kurtosis-1.1900216
Mean83418.821
Median Absolute Deviation (MAD)17554
Skewness-0.002844719
Sum8.3418821 × 108
Variance4.1266345 × 108
MonotonicityNot monotonic
2024-04-17T19:03:13.960562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53483 1
 
< 0.1%
102191 1
 
< 0.1%
56341 1
 
< 0.1%
87738 1
 
< 0.1%
62850 1
 
< 0.1%
105438 1
 
< 0.1%
90948 1
 
< 0.1%
108874 1
 
< 0.1%
87158 1
 
< 0.1%
89680 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
47955 1
< 0.1%
47957 1
< 0.1%
47961 1
< 0.1%
47962 1
< 0.1%
47964 1
< 0.1%
47984 1
< 0.1%
47995 1
< 0.1%
48002 1
< 0.1%
48003 1
< 0.1%
48013 1
< 0.1%
ValueCountFrequency (%)
118536 1
< 0.1%
118532 1
< 0.1%
118529 1
< 0.1%
118523 1
< 0.1%
118519 1
< 0.1%
118517 1
< 0.1%
118515 1
< 0.1%
118506 1
< 0.1%
118503 1
< 0.1%
118495 1
< 0.1%

ccode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.4817
Minimum108
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:14.105776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile113
Q1125
median134
Q3143
95-th percentile151
Maximum152
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.647525
Coefficient of variation (CV)0.087259337
Kurtosis-0.93194195
Mean133.4817
Median Absolute Deviation (MAD)9
Skewness-0.25946375
Sum1334817
Variance135.66483
MonotonicityNot monotonic
2024-04-17T19:03:14.231189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
142 323
 
3.2%
143 317
 
3.2%
122 310
 
3.1%
125 303
 
3.0%
151 300
 
3.0%
135 295
 
2.9%
148 292
 
2.9%
139 290
 
2.9%
134 288
 
2.9%
123 287
 
2.9%
Other values (35) 6995
70.0%
ValueCountFrequency (%)
108 74
 
0.7%
109 1
 
< 0.1%
110 87
 
0.9%
111 5
 
0.1%
112 228
2.3%
113 211
2.1%
114 196
2.0%
115 190
1.9%
116 161
1.6%
117 121
1.2%
ValueCountFrequency (%)
152 253
2.5%
151 300
3.0%
150 248
2.5%
149 282
2.8%
148 292
2.9%
147 273
2.7%
146 278
2.8%
145 162
1.6%
144 258
2.6%
143 317
3.2%

pcode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.4817
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:14.359939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1123
median132
Q3141
95-th percentile149
Maximum150
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.647525
Coefficient of variation (CV)0.08858666
Kurtosis-0.93194195
Mean131.4817
Median Absolute Deviation (MAD)9
Skewness-0.25946375
Sum1314817
Variance135.66483
MonotonicityNot monotonic
2024-04-17T19:03:14.483635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
140 323
 
3.2%
141 317
 
3.2%
120 310
 
3.1%
123 303
 
3.0%
149 300
 
3.0%
133 295
 
2.9%
146 292
 
2.9%
137 290
 
2.9%
132 288
 
2.9%
121 287
 
2.9%
Other values (35) 6995
70.0%
ValueCountFrequency (%)
106 74
 
0.7%
107 1
 
< 0.1%
108 87
 
0.9%
109 5
 
0.1%
110 228
2.3%
111 211
2.1%
112 196
2.0%
113 190
1.9%
114 161
1.6%
115 121
1.2%
ValueCountFrequency (%)
150 253
2.5%
149 300
3.0%
148 248
2.5%
147 282
2.8%
146 292
2.9%
145 273
2.7%
144 278
2.8%
143 162
1.6%
142 258
2.6%
141 317
3.2%

bssh_no
Real number (ℝ)

MISSING 

Distinct676
Distinct (%)7.6%
Missing1103
Missing (%)11.0%
Infinite0
Infinite (%)0.0%
Mean2139.9536
Minimum985
Maximum3199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:14.888790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum985
5-th percentile1045
Q11534
median2025
Q32791
95-th percentile3051
Maximum3199
Range2214
Interquartile range (IQR)1257

Descriptive statistics

Standard deviation677.29507
Coefficient of variation (CV)0.31649989
Kurtosis-1.3907595
Mean2139.9536
Median Absolute Deviation (MAD)663
Skewness-0.10097308
Sum19039167
Variance458728.61
MonotonicityNot monotonic
2024-04-17T19:03:15.006240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1798 70
 
0.7%
1140 54
 
0.5%
2002 51
 
0.5%
2693 51
 
0.5%
1981 50
 
0.5%
1650 45
 
0.4%
1766 45
 
0.4%
2982 44
 
0.4%
1930 43
 
0.4%
1350 42
 
0.4%
Other values (666) 8402
84.0%
(Missing) 1103
 
11.0%
ValueCountFrequency (%)
985 11
 
0.1%
986 7
 
0.1%
988 23
0.2%
991 8
 
0.1%
996 34
0.3%
997 13
 
0.1%
998 10
 
0.1%
999 16
0.2%
1004 22
0.2%
1012 13
 
0.1%
ValueCountFrequency (%)
3199 1
 
< 0.1%
3195 1
 
< 0.1%
3193 1
 
< 0.1%
3192 2
< 0.1%
3187 4
< 0.1%
3186 2
< 0.1%
3185 1
 
< 0.1%
3184 2
< 0.1%
3182 1
 
< 0.1%
3178 2
< 0.1%

search_no
Real number (ℝ)

Distinct8950
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean478490.43
Minimum456028
Maximum509102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:15.131122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456028
5-th percentile457822.95
Q1466122.5
median475969.5
Q3491512.25
95-th percentile504857.25
Maximum509102
Range53074
Interquartile range (IQR)25389.75

Descriptive statistics

Standard deviation14851.212
Coefficient of variation (CV)0.031037637
Kurtosis-1.1145627
Mean478490.43
Median Absolute Deviation (MAD)11600
Skewness0.33288681
Sum4.7849043 × 109
Variance2.205585 × 108
MonotonicityNot monotonic
2024-04-17T19:03:15.266827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
463771 6
 
0.1%
468534 5
 
0.1%
470855 5
 
0.1%
463095 5
 
0.1%
470841 5
 
0.1%
469619 5
 
0.1%
471675 5
 
0.1%
464596 5
 
0.1%
466169 4
 
< 0.1%
457116 4
 
< 0.1%
Other values (8940) 9951
99.5%
ValueCountFrequency (%)
456028 1
< 0.1%
456029 1
< 0.1%
456032 1
< 0.1%
456034 1
< 0.1%
456038 2
< 0.1%
456039 2
< 0.1%
456046 1
< 0.1%
456047 1
< 0.1%
456055 1
< 0.1%
456057 1
< 0.1%
ValueCountFrequency (%)
509102 1
< 0.1%
509091 1
< 0.1%
509086 1
< 0.1%
509080 1
< 0.1%
509066 1
< 0.1%
509065 1
< 0.1%
509057 1
< 0.1%
509048 1
< 0.1%
509046 1
< 0.1%
509042 1
< 0.1%

prices_no
Real number (ℝ)

Distinct8950
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean478490.43
Minimum456028
Maximum509102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:15.395360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456028
5-th percentile457822.95
Q1466122.5
median475969.5
Q3491512.25
95-th percentile504857.25
Maximum509102
Range53074
Interquartile range (IQR)25389.75

Descriptive statistics

Standard deviation14851.212
Coefficient of variation (CV)0.031037637
Kurtosis-1.1145627
Mean478490.43
Median Absolute Deviation (MAD)11600
Skewness0.33288681
Sum4.7849043 × 109
Variance2.205585 × 108
MonotonicityNot monotonic
2024-04-17T19:03:15.520854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
463771 6
 
0.1%
468534 5
 
0.1%
470855 5
 
0.1%
463095 5
 
0.1%
470841 5
 
0.1%
469619 5
 
0.1%
471675 5
 
0.1%
464596 5
 
0.1%
466169 4
 
< 0.1%
457116 4
 
< 0.1%
Other values (8940) 9951
99.5%
ValueCountFrequency (%)
456028 1
< 0.1%
456029 1
< 0.1%
456032 1
< 0.1%
456034 1
< 0.1%
456038 2
< 0.1%
456039 2
< 0.1%
456046 1
< 0.1%
456047 1
< 0.1%
456055 1
< 0.1%
456057 1
< 0.1%
ValueCountFrequency (%)
509102 1
< 0.1%
509091 1
< 0.1%
509086 1
< 0.1%
509080 1
< 0.1%
509066 1
< 0.1%
509065 1
< 0.1%
509057 1
< 0.1%
509048 1
< 0.1%
509046 1
< 0.1%
509042 1
< 0.1%

prdlst
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.4817
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:15.654512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1123
median132
Q3141
95-th percentile149
Maximum150
Range44
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.647525
Coefficient of variation (CV)0.08858666
Kurtosis-0.93194195
Mean131.4817
Median Absolute Deviation (MAD)9
Skewness-0.25946375
Sum1314817
Variance135.66483
MonotonicityNot monotonic
2024-04-17T19:03:15.776368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
140 323
 
3.2%
141 317
 
3.2%
120 310
 
3.1%
123 303
 
3.0%
149 300
 
3.0%
133 295
 
2.9%
146 292
 
2.9%
137 290
 
2.9%
132 288
 
2.9%
121 287
 
2.9%
Other values (35) 6995
70.0%
ValueCountFrequency (%)
106 74
 
0.7%
107 1
 
< 0.1%
108 87
 
0.9%
109 5
 
0.1%
110 228
2.3%
111 211
2.1%
112 196
2.0%
113 190
1.9%
114 161
1.6%
115 121
1.2%
ValueCountFrequency (%)
150 253
2.5%
149 300
3.0%
148 248
2.5%
147 282
2.8%
146 292
2.9%
145 273
2.7%
144 278
2.8%
143 162
1.6%
142 258
2.6%
141 317
3.2%

cl_no
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
419
8897 
<NA>
1103 

Length

Max length4
Median length3
Mean length3.1103
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row419
2nd row419
3rd row419
4th row419
5th row419

Common Values

ValueCountFrequency (%)
419 8897
89.0%
<NA> 1103
 
11.0%

Length

2024-04-17T19:03:15.889922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:15.980297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
419 8897
89.0%
na 1103
 
11.0%

examin_de
Date

Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-06-12 00:00:00
Maximum2020-11-10 00:00:00
2024-04-17T19:03:16.078880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:03:16.203946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

pum_cd
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
454
5941 
466
2257 
465
1202 
455
 
526
467
 
74

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row466
2nd row454
3rd row454
4th row454
5th row465

Common Values

ValueCountFrequency (%)
454 5941
59.4%
466 2257
 
22.6%
465 1202
 
12.0%
455 526
 
5.3%
467 74
 
0.7%

Length

2024-04-17T19:03:16.332861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:16.454054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
454 5941
59.4%
466 2257
 
22.6%
465 1202
 
12.0%
455 526
 
5.3%
467 74
 
0.7%

pum_nm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
외식
5941 
서비스
2257 
여가생활
1202 
카페
 
526
기타
 
74

Length

Max length4
Median length2
Mean length2.4661
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서비스
2nd row외식
3rd row외식
4th row외식
5th row여가생활

Common Values

ValueCountFrequency (%)
외식 5941
59.4%
서비스 2257
 
22.6%
여가생활 1202
 
12.0%
카페 526
 
5.3%
기타 74
 
0.7%

Length

2024-04-17T19:03:16.567878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:16.668927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식 5941
59.4%
서비스 2257
 
22.6%
여가생활 1202
 
12.0%
카페 526
 
5.3%
기타 74
 
0.7%

gugun_cd
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)0.8%
Missing1106
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean176.82471
Minimum31
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:16.775224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile41
Q190
median176
Q3261
95-th percentile373
Maximum376
Range345
Interquartile range (IQR)171

Descriptive statistics

Standard deviation105.75119
Coefficient of variation (CV)0.59805663
Kurtosis-1.0063681
Mean176.82471
Median Absolute Deviation (MAD)85
Skewness0.39434047
Sum1572679
Variance11183.314
MonotonicityNot monotonic
2024-04-17T19:03:16.893412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
373 748
 
7.5%
189 681
 
6.8%
48 631
 
6.3%
275 628
 
6.3%
216 517
 
5.2%
41 449
 
4.5%
135 403
 
4.0%
178 344
 
3.4%
57 332
 
3.3%
92 316
 
3.2%
Other values (63) 3845
38.5%
(Missing) 1106
 
11.1%
ValueCountFrequency (%)
31 11
 
0.1%
39 11
 
0.1%
40 162
 
1.6%
41 449
4.5%
42 28
 
0.3%
45 13
 
0.1%
48 631
6.3%
53 96
 
1.0%
54 27
 
0.3%
57 332
3.3%
ValueCountFrequency (%)
376 2
 
< 0.1%
373 748
7.5%
372 8
 
0.1%
370 18
 
0.2%
369 69
 
0.7%
365 14
 
0.1%
350 15
 
0.1%
346 42
 
0.4%
345 6
 
0.1%
344 10
 
0.1%

gugun_nm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
1106 
해운대구
859 
부산진구
780 
연제구
760 
동래구
756 
Other values (9)
5739 

Length

Max length4
Median length3
Mean length3.0282
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수영구
2nd row기장군
3rd row사상구
4th row중구
5th row부산진구

Common Values

ValueCountFrequency (%)
<NA> 1106
11.1%
해운대구 859
 
8.6%
부산진구 780
 
7.8%
연제구 760
 
7.6%
동래구 756
 
7.6%
북구 702
 
7.0%
사하구 683
 
6.8%
사상구 681
 
6.8%
금정구 661
 
6.6%
남구 650
 
6.5%
Other values (4) 2362
23.6%

Length

2024-04-17T19:03:17.015426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1106
11.1%
해운대구 859
 
8.6%
부산진구 780
 
7.8%
연제구 760
 
7.6%
동래구 756
 
7.6%
북구 702
 
7.0%
사하구 683
 
6.8%
사상구 681
 
6.8%
금정구 661
 
6.6%
남구 650
 
6.5%
Other values (4) 2362
23.6%

unit
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.0728
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:17.121936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile200
Maximum350
Range349
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55.794269
Coefficient of variation (CV)2.9253318
Kurtosis7.1149338
Mean19.0728
Median Absolute Deviation (MAD)0
Skewness2.9168835
Sum190728
Variance3113.0004
MonotonicityNot monotonic
2024-04-17T19:03:17.243342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 9008
90.1%
200 708
 
7.1%
120 80
 
0.8%
130 73
 
0.7%
100 37
 
0.4%
150 32
 
0.3%
180 19
 
0.2%
350 14
 
0.1%
170 13
 
0.1%
110 8
 
0.1%
ValueCountFrequency (%)
1 9008
90.1%
100 37
 
0.4%
110 8
 
0.1%
120 80
 
0.8%
130 73
 
0.7%
140 8
 
0.1%
150 32
 
0.3%
170 13
 
0.1%
180 19
 
0.2%
200 708
 
7.1%
ValueCountFrequency (%)
350 14
 
0.1%
200 708
7.1%
180 19
 
0.2%
170 13
 
0.1%
150 32
 
0.3%
140 8
 
0.1%
130 73
 
0.7%
120 80
 
0.8%
110 8
 
0.1%
100 37
 
0.4%

unitprice
Real number (ℝ)

ZEROS 

Distinct204
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12198.489
Minimum0
Maximum229900
Zeros588
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:17.361374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13900
median7000
Q312307
95-th percentile40000
Maximum229900
Range229900
Interquartile range (IQR)8407

Descriptive statistics

Standard deviation22190.918
Coefficient of variation (CV)1.819153
Kurtosis38.651132
Mean12198.489
Median Absolute Deviation (MAD)4000
Skewness5.6901283
Sum1.2198489 × 108
Variance4.9243683 × 108
MonotonicityNot monotonic
2024-04-17T19:03:17.480565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000 860
 
8.6%
5000 653
 
6.5%
7000 648
 
6.5%
0 588
 
5.9%
3000 571
 
5.7%
15000 467
 
4.7%
10000 442
 
4.4%
9000 416
 
4.2%
8000 324
 
3.2%
12000 282
 
2.8%
Other values (194) 4749
47.5%
ValueCountFrequency (%)
0 588
5.9%
35 1
 
< 0.1%
200 13
 
0.1%
250 7
 
0.1%
300 39
 
0.4%
350 30
 
0.3%
450 16
 
0.2%
500 36
 
0.4%
800 2
 
< 0.1%
1000 73
 
0.7%
ValueCountFrequency (%)
229900 2
 
< 0.1%
217800 7
 
0.1%
210000 5
 
0.1%
205700 2
 
< 0.1%
200000 23
0.2%
190000 14
0.1%
180000 5
 
0.1%
179000 1
 
< 0.1%
173300 1
 
< 0.1%
170400 1
 
< 0.1%

prices
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

rm
Text

MISSING 

Distinct97
Distinct (%)14.7%
Missing9340
Missing (%)93.4%
Memory size156.2 KiB
2024-04-17T19:03:17.703353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length7.2363636
Min length1

Characters and Unicode

Total characters4776
Distinct characters187
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)1.4%

Sample

1st row미스트피자콤보 R
2nd row한우등심 200g
3rd row찹쌀탕수육 중
4th row주말30000
5th row양복바지밑단줄임
ValueCountFrequency (%)
재개발지역으로페업 31
 
3.6%
주말 27
 
3.2%
비회원 26
 
3.1%
1300 26
 
3.1%
50000 24
 
2.8%
페업 23
 
2.7%
인상 19
 
2.2%
주말30000 17
 
2.0%
10분 17
 
2.0%
초급 16
 
1.9%
Other values (101) 625
73.4%
2024-04-17T19:03:18.071207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 777
 
16.3%
292
 
6.1%
1 181
 
3.8%
원 167
 
3.5%
3 99
 
2.1%
/ 97
 
2.0%
업 91
 
1.9%
2 84
 
1.8%
페 77
 
1.6%
5 76
 
1.6%
Other values (177) 2835
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2860
59.9%
Decimal Number 1337
28.0%
Space Separator 292
 
6.1%
Other Punctuation 165
 
3.5%
Lowercase Letter 57
 
1.2%
Open Punctuation 22
 
0.5%
Close Punctuation 22
 
0.5%
Math Symbol 12
 
0.3%
Uppercase Letter 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 167
 
5.8%
업 91
 
3.2%
페 77
 
2.7%
주 70
 
2.4%
인 68
 
2.4%
개 64
 
2.2%
이 62
 
2.2%
지 61
 
2.1%
로 56
 
2.0%
분 55
 
1.9%
Other values (152) 2089
73.0%
Decimal Number
ValueCountFrequency (%)
0 777
58.1%
1 181
 
13.5%
3 99
 
7.4%
2 84
 
6.3%
5 76
 
5.7%
9 49
 
3.7%
4 40
 
3.0%
7 18
 
1.3%
6 11
 
0.8%
8 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 97
58.8%
, 44
26.7%
: 15
 
9.1%
% 5
 
3.0%
. 3
 
1.8%
* 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
g 45
78.9%
k 10
 
17.5%
c 1
 
1.8%
m 1
 
1.8%
Space Separator
ValueCountFrequency (%)
292
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2845
59.6%
Common 1850
38.7%
Latin 66
 
1.4%
Han 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 167
 
5.9%
업 91
 
3.2%
페 77
 
2.7%
주 70
 
2.5%
인 68
 
2.4%
개 64
 
2.2%
이 62
 
2.2%
지 61
 
2.1%
로 56
 
2.0%
분 55
 
1.9%
Other values (150) 2074
72.9%
Common
ValueCountFrequency (%)
0 777
42.0%
292
 
15.8%
1 181
 
9.8%
3 99
 
5.4%
/ 97
 
5.2%
2 84
 
4.5%
5 76
 
4.1%
9 49
 
2.6%
, 44
 
2.4%
4 40
 
2.2%
Other values (10) 111
 
6.0%
Latin
ValueCountFrequency (%)
g 45
68.2%
k 10
 
15.2%
R 9
 
13.6%
c 1
 
1.5%
m 1
 
1.5%
Han
ValueCountFrequency (%)
大 10
66.7%
小 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2845
59.6%
ASCII 1916
40.1%
CJK 15
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 777
40.6%
292
 
15.2%
1 181
 
9.4%
3 99
 
5.2%
/ 97
 
5.1%
2 84
 
4.4%
5 76
 
4.0%
9 49
 
2.6%
g 45
 
2.3%
, 44
 
2.3%
Other values (15) 172
 
9.0%
Hangul
ValueCountFrequency (%)
원 167
 
5.9%
업 91
 
3.2%
페 77
 
2.7%
주 70
 
2.5%
인 68
 
2.4%
개 64
 
2.2%
이 62
 
2.2%
지 61
 
2.1%
로 56
 
2.0%
분 55
 
1.9%
Other values (150) 2074
72.9%
CJK
ValueCountFrequency (%)
大 10
66.7%
小 5
33.3%

bssh_nm
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

la
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

lo
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

adres
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

telno
Text

MISSING 

Distinct669
Distinct (%)7.5%
Missing1103
Missing (%)11.0%
Memory size156.2 KiB
2024-04-17T19:03:18.297011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.024952
Min length10

Characters and Unicode

Total characters106986
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st row051-628-0028
2nd row051-727-7666
3rd row051-317-2478
4th row051-245-2310
5th row010-3757-0045
ValueCountFrequency (%)
051-207-1472 70
 
0.8%
051-611-5727 54
 
0.6%
051-559-1592 52
 
0.6%
051-866-9612 51
 
0.6%
051-622-2234 51
 
0.6%
051-864-9090 50
 
0.6%
051-326-2747 45
 
0.5%
051-332-0551 45
 
0.5%
051-612-3808 44
 
0.5%
051-625-5558 43
 
0.5%
Other values (659) 8392
94.3%
2024-04-17T19:03:18.652057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17420
16.3%
0 16730
15.6%
5 15912
14.9%
1 14183
13.3%
2 8469
7.9%
7 6866
 
6.4%
3 6277
 
5.9%
8 6134
 
5.7%
6 6048
 
5.7%
4 5389
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89566
83.7%
Dash Punctuation 17420
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16730
18.7%
5 15912
17.8%
1 14183
15.8%
2 8469
9.5%
7 6866
7.7%
3 6277
 
7.0%
8 6134
 
6.8%
6 6048
 
6.8%
4 5389
 
6.0%
9 3558
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 17420
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106986
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17420
16.3%
0 16730
15.6%
5 15912
14.9%
1 14183
13.3%
2 8469
7.9%
7 6866
 
6.4%
3 6277
 
5.9%
8 6134
 
5.7%
6 6048
 
5.7%
4 5389
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17420
16.3%
0 16730
15.6%
5 15912
14.9%
1 14183
13.3%
2 8469
7.9%
7 6866
 
6.4%
3 6277
 
5.9%
8 6134
 
5.7%
6 6048
 
5.7%
4 5389
 
5.0%

parkng_at
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
6043 
Y
2854 
755 
<NA>
 
348

Length

Max length4
Median length1
Mean length1.1044
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowN
5th rowN

Common Values

ValueCountFrequency (%)
N 6043
60.4%
Y 2854
28.5%
755
 
7.5%
<NA> 348
 
3.5%

Length

2024-04-17T19:03:18.800141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:18.889810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6043
65.4%
y 2854
30.9%
na 348
 
3.8%

card_at
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
8432 
 
755
N
 
465
<NA>
 
348

Length

Max length4
Median length1
Mean length1.1044
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 8432
84.3%
755
 
7.5%
N 465
 
4.7%
<NA> 348
 
3.5%

Length

2024-04-17T19:03:18.987279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:19.073642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 8432
91.2%
n 465
 
5.0%
na 348
 
3.8%

item_name
Categorical

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
삼겹살(외식)
 
323
돼지갈비(외식)
 
317
PC방 이용료
 
310
양복세탁료
 
303
냉면
 
300
Other values (41)
8447 

Length

Max length8
Median length7
Mean length4.196
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row목욕료
2nd row피자
3rd row돼지국밥
4th row냉면
5th rowPC방 이용료

Common Values

ValueCountFrequency (%)
삼겹살(외식) 323
 
3.2%
돼지갈비(외식) 317
 
3.2%
PC방 이용료 310
 
3.1%
양복세탁료 303
 
3.0%
냉면 300
 
3.0%
탕수육 295
 
2.9%
삼계탕 292
 
2.9%
돈가스 290
 
2.9%
칼국수 288
 
2.9%
노래방이용료 287
 
2.9%
Other values (36) 6995
70.0%

Length

2024-04-17T19:03:19.180823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용료 628
 
6.1%
삼겹살(외식 323
 
3.1%
돼지갈비(외식 317
 
3.1%
pc방 310
 
3.0%
양복세탁료 303
 
2.9%
냉면 300
 
2.9%
탕수육 295
 
2.8%
삼계탕 292
 
2.8%
돈가스 290
 
2.8%
칼국수 288
 
2.8%
Other values (36) 7022
67.7%

last_load_dttm
Date

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-06 10:52:29
Maximum2021-01-06 10:52:40
2024-04-17T19:03:19.291527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:03:19.390018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Sample

skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
447215348312712519344627874627871254192018-10-02466서비스261수영구16000<NA><NA><NA><NA><NA><NA>051-628-0028NY목욕료2021-01-06 10:52:36
6444211237013613424244583714583711344192018-07-10454외식48기장군117900<NA>미스트피자콤보 R<NA><NA><NA><NA>051-727-7666YY피자2021-01-06 10:52:39
125278571614514331124897674897671434192020-01-07454외식189사상구18000<NA><NA><NA><NA><NA><NA>051-317-2478YY돼지국밥2021-01-06 10:52:31
53259295315114922684943234943231494192020-03-17454외식350중구111000<NA><NA><NA><NA><NA><NA>051-245-2310NY냉면2021-01-06 10:52:30
110168725912212014964914484914481204192020-02-04465여가생활135부산진구11000<NA><NA><NA><NA><NA><NA>010-3757-0045NYPC방 이용료2021-01-06 10:52:31
5344610137913012816205017595017591284192020-07-21466서비스176북구140000<NA><NA><NA><NA><NA><NA>051-335-1960NY숙박료(여관)2021-01-06 10:52:37
161758202115014829704863844863841484192019-11-12454외식275연제구15000<NA><NA><NA><NA><NA><NA>0518537999NY비빔밥2021-01-06 10:52:31
349016336714013819984715804715801384192019-03-05454외식275연제구13000<NA><NA><NA><NA><NA><NA>051-867-2324NY조리라면2021-01-06 10:52:34
73529088214214026984925004925001404192020-02-18454외식59남구20013000<NA><NA><NA><NA><NA><NA>010-9329-8328YY삼겹살(외식)2021-01-06 10:52:30
146538355414614416504876634876631444192019-11-26454외식178북구15000<NA><NA><NA><NA><NA><NA>051-332-0551NY된장찌개백반2021-01-06 10:52:31
skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
179188033012912711644847394847391274192019-10-15466서비스57남구112000<NA><NA><NA><NA><NA><NA>051-624-0440NY이용료2021-01-06 10:52:32
3975058517124122<NA>467224467224122<NA>2018-12-11465여가생활<NA><NA>112000<NA><NA><NA><NA><NA><NA><NA>당구장이용료2021-01-06 10:52:35
6644811437814214029274683224683221404192019-01-08454외식59남구20012000<NA><NA><NA><NA><NA><NA>051-611-2280NY삼겹살(외식)2021-01-06 10:52:39
483284990613613416614992734992731344192020-06-09454외식178북구123900<NA><NA><NA><NA><NA><NA>051-335-5202NY피자2021-01-06 10:52:36
39759426614113919784955784955781394192020-04-14454외식275연제구13000<NA><NA><NA><NA><NA><NA>051-865-9339NY자장면2021-01-06 10:52:29
60209221814514331504936264936261434192020-03-03454외식178북구17000<NA><NA><NA><NA><NA><NA>051-337-1711NY돼지국밥2021-01-06 10:52:30
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