Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells61124
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory233.0 B

Variable types

Numeric10
Categorical8
DateTime1
Unsupported5
Text2

Alerts

cl_no is highly imbalanced (66.5%)Imbalance
card_at is highly imbalanced (51.6%)Imbalance
bssh_no has 618 (6.2%) missing valuesMissing
gugun_cd has 675 (6.8%) missing valuesMissing
prices has 10000 (100.0%) missing valuesMissing
rm has 9213 (92.1%) 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 618 (6.2%) 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 245 (2.5%) zerosZeros

Reproduction

Analysis started2023-10-09 11:59:49.828319
Analysis finished2023-10-09 11:59:50.952133
Duration1.12 second
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%
Mean243850.44
Minimum208812
Maximum279138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:51.100673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum208812
5-th percentile212514.9
Q1226491
median243851
Q3261264
95-th percentile275421.2
Maximum279138
Range70326
Interquartile range (IQR)34773

Descriptive statistics

Standard deviation20193.044
Coefficient of variation (CV)0.082809138
Kurtosis-1.1951111
Mean243850.44
Median Absolute Deviation (MAD)17388.5
Skewness-0.0011340591
Sum2.4385044 × 109
Variance4.0775904 × 108
MonotonicityNot monotonic
2023-10-09T20:59:51.380862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
213707 1
 
< 0.1%
260881 1
 
< 0.1%
275065 1
 
< 0.1%
236299 1
 
< 0.1%
220763 1
 
< 0.1%
237826 1
 
< 0.1%
248293 1
 
< 0.1%
211000 1
 
< 0.1%
213888 1
 
< 0.1%
213907 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
208812 1
< 0.1%
208820 1
< 0.1%
208841 1
< 0.1%
208859 1
< 0.1%
208861 1
< 0.1%
208862 1
< 0.1%
208864 1
< 0.1%
208865 1
< 0.1%
208876 1
< 0.1%
208882 1
< 0.1%
ValueCountFrequency (%)
279138 1
< 0.1%
278840 1
< 0.1%
278817 1
< 0.1%
278811 1
< 0.1%
278793 1
< 0.1%
278790 1
< 0.1%
278786 1
< 0.1%
278780 1
< 0.1%
278779 1
< 0.1%
278778 1
< 0.1%

ccode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.0929
Minimum108
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:51.668074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile113
Q1124
median134
Q3143
95-th percentile150
Maximum152
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.662919
Coefficient of variation (CV)0.087629909
Kurtosis-0.94651199
Mean133.0929
Median Absolute Deviation (MAD)9
Skewness-0.24147293
Sum1330929
Variance136.02367
MonotonicityNot monotonic
2023-10-09T20:59:51.943504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
143 334
 
3.3%
132 318
 
3.2%
142 316
 
3.2%
135 305
 
3.0%
122 301
 
3.0%
137 301
 
3.0%
141 299
 
3.0%
125 299
 
3.0%
128 287
 
2.9%
124 282
 
2.8%
Other values (35) 6958
69.6%
ValueCountFrequency (%)
108 82
 
0.8%
109 9
 
0.1%
110 101
1.0%
111 12
 
0.1%
112 222
2.2%
113 197
2.0%
114 203
2.0%
115 247
2.5%
116 158
1.6%
117 133
1.3%
ValueCountFrequency (%)
152 223
2.2%
151 238
2.4%
150 270
2.7%
149 239
2.4%
148 277
2.8%
147 267
2.7%
146 272
2.7%
145 232
2.3%
144 258
2.6%
143 334
3.3%

pcode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.0929
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:52.213429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1122
median132
Q3141
95-th percentile148
Maximum150
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.662919
Coefficient of variation (CV)0.088966822
Kurtosis-0.94651199
Mean131.0929
Median Absolute Deviation (MAD)9
Skewness-0.24147293
Sum1310929
Variance136.02367
MonotonicityNot monotonic
2023-10-09T20:59:52.485369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 334
 
3.3%
130 318
 
3.2%
140 316
 
3.2%
133 305
 
3.0%
120 301
 
3.0%
135 301
 
3.0%
139 299
 
3.0%
123 299
 
3.0%
126 287
 
2.9%
122 282
 
2.8%
Other values (35) 6958
69.6%
ValueCountFrequency (%)
106 82
 
0.8%
107 9
 
0.1%
108 101
1.0%
109 12
 
0.1%
110 222
2.2%
111 197
2.0%
112 203
2.0%
113 247
2.5%
114 158
1.6%
115 133
1.3%
ValueCountFrequency (%)
150 223
2.2%
149 238
2.4%
148 270
2.7%
147 239
2.4%
146 277
2.8%
145 267
2.7%
144 272
2.7%
143 232
2.3%
142 258
2.6%
141 334
3.3%

bssh_no
Real number (ℝ)

MISSING 

Distinct708
Distinct (%)7.5%
Missing618
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean2244.9397
Minimum985
Maximum3259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:52.729452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum985
5-th percentile1055
Q11579
median2407
Q32950
95-th percentile3161
Maximum3259
Range2274
Interquartile range (IQR)1371

Descriptive statistics

Standard deviation717.37927
Coefficient of variation (CV)0.31955392
Kurtosis-1.4194749
Mean2244.9397
Median Absolute Deviation (MAD)617
Skewness-0.23019985
Sum21062024
Variance514633.02
MonotonicityNot monotonic
2023-10-09T20:59:53.010872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1140 62
 
0.6%
2693 60
 
0.6%
2982 51
 
0.5%
1766 46
 
0.5%
1261 45
 
0.4%
1146 44
 
0.4%
2963 43
 
0.4%
2733 42
 
0.4%
2443 42
 
0.4%
1981 41
 
0.4%
Other values (698) 8906
89.1%
(Missing) 618
 
6.2%
ValueCountFrequency (%)
985 11
 
0.1%
986 12
 
0.1%
988 10
 
0.1%
991 16
0.2%
996 37
0.4%
997 13
 
0.1%
998 11
 
0.1%
999 9
 
0.1%
1004 24
0.2%
1012 8
 
0.1%
ValueCountFrequency (%)
3259 2
 
< 0.1%
3258 1
 
< 0.1%
3256 4
< 0.1%
3254 1
 
< 0.1%
3251 2
 
< 0.1%
3250 5
0.1%
3248 1
 
< 0.1%
3246 3
< 0.1%
3245 2
 
< 0.1%
3243 3
< 0.1%

search_no
Real number (ℝ)

Distinct8653
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean509639.22
Minimum462126
Maximum547771
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:53.343485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum462126
5-th percentile464299.8
Q1501863.25
median511526.5
Q3527080
95-th percentile542752.5
Maximum547771
Range85645
Interquartile range (IQR)25216.75

Descriptive statistics

Standard deviation23685.909
Coefficient of variation (CV)0.046475837
Kurtosis-0.44039091
Mean509639.22
Median Absolute Deviation (MAD)11060
Skewness-0.57366167
Sum5.0963922 × 109
Variance5.610223 × 108
MonotonicityNot monotonic
2023-10-09T20:59:53.948229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
463864 7
 
0.1%
503648 5
 
0.1%
502691 5
 
0.1%
542178 5
 
0.1%
464226 5
 
0.1%
464389 5
 
0.1%
503734 5
 
0.1%
527162 5
 
0.1%
517678 5
 
0.1%
511256 5
 
0.1%
Other values (8643) 9948
99.5%
ValueCountFrequency (%)
462126 1
< 0.1%
462133 1
< 0.1%
462148 1
< 0.1%
462162 1
< 0.1%
462164 2
< 0.1%
462165 1
< 0.1%
462166 1
< 0.1%
462175 1
< 0.1%
462176 1
< 0.1%
462178 1
< 0.1%
ValueCountFrequency (%)
547771 1
< 0.1%
547766 1
< 0.1%
547752 1
< 0.1%
547738 1
< 0.1%
547730 1
< 0.1%
547725 1
< 0.1%
547724 1
< 0.1%
547723 1
< 0.1%
547722 1
< 0.1%
547721 1
< 0.1%

prices_no
Real number (ℝ)

Distinct8653
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean509639.22
Minimum462126
Maximum547771
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:54.204606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum462126
5-th percentile464299.8
Q1501863.25
median511526.5
Q3527080
95-th percentile542752.5
Maximum547771
Range85645
Interquartile range (IQR)25216.75

Descriptive statistics

Standard deviation23685.909
Coefficient of variation (CV)0.046475837
Kurtosis-0.44039091
Mean509639.22
Median Absolute Deviation (MAD)11060
Skewness-0.57366167
Sum5.0963922 × 109
Variance5.610223 × 108
MonotonicityNot monotonic
2023-10-09T20:59:54.590228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
463864 7
 
0.1%
503648 5
 
0.1%
502691 5
 
0.1%
542178 5
 
0.1%
464226 5
 
0.1%
464389 5
 
0.1%
503734 5
 
0.1%
527162 5
 
0.1%
517678 5
 
0.1%
511256 5
 
0.1%
Other values (8643) 9948
99.5%
ValueCountFrequency (%)
462126 1
< 0.1%
462133 1
< 0.1%
462148 1
< 0.1%
462162 1
< 0.1%
462164 2
< 0.1%
462165 1
< 0.1%
462166 1
< 0.1%
462175 1
< 0.1%
462176 1
< 0.1%
462178 1
< 0.1%
ValueCountFrequency (%)
547771 1
< 0.1%
547766 1
< 0.1%
547752 1
< 0.1%
547738 1
< 0.1%
547730 1
< 0.1%
547725 1
< 0.1%
547724 1
< 0.1%
547723 1
< 0.1%
547722 1
< 0.1%
547721 1
< 0.1%

prdlst
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.0929
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:54.889007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile111
Q1122
median132
Q3141
95-th percentile148
Maximum150
Range44
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.662919
Coefficient of variation (CV)0.088966822
Kurtosis-0.94651199
Mean131.0929
Median Absolute Deviation (MAD)9
Skewness-0.24147293
Sum1310929
Variance136.02367
MonotonicityNot monotonic
2023-10-09T20:59:55.263233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
141 334
 
3.3%
130 318
 
3.2%
140 316
 
3.2%
133 305
 
3.0%
120 301
 
3.0%
135 301
 
3.0%
139 299
 
3.0%
123 299
 
3.0%
126 287
 
2.9%
122 282
 
2.8%
Other values (35) 6958
69.6%
ValueCountFrequency (%)
106 82
 
0.8%
107 9
 
0.1%
108 101
1.0%
109 12
 
0.1%
110 222
2.2%
111 197
2.0%
112 203
2.0%
113 247
2.5%
114 158
1.6%
115 133
1.3%
ValueCountFrequency (%)
150 223
2.2%
149 238
2.4%
148 270
2.7%
147 239
2.4%
146 277
2.8%
145 267
2.7%
144 272
2.7%
143 232
2.3%
142 258
2.6%
141 334
3.3%

cl_no
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
419
9382 
<NA>
 
618

Length

Max length4
Median length3
Mean length3.0618
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
419 9382
93.8%
<NA> 618
 
6.2%

Length

2023-10-09T20:59:55.612779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-09T20:59:55.794677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
419 9382
93.8%
na 618
 
6.2%

examin_de
Date

Distinct73
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-09-18 00:00:00
Maximum2022-08-23 00:00:00
2023-10-09T20:59:56.030509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-10-09T20:59:56.276127image/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
5764 
466
2380 
465
1198 
455
 
576
467
 
82

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row455
2nd row454
3rd row466
4th row466
5th row454

Common Values

ValueCountFrequency (%)
454 5764
57.6%
466 2380
23.8%
465 1198
 
12.0%
455 576
 
5.8%
467 82
 
0.8%

Length

2023-10-09T20:59:56.511344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-09T20:59:56.762418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
454 5764
57.6%
466 2380
23.8%
465 1198
 
12.0%
455 576
 
5.8%
467 82
 
0.8%

pum_nm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
외식
5764 
서비스
2380 
여가생활
1198 
카페
 
576
기타
 
82

Length

Max length4
Median length2
Mean length2.4776
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외식 5764
57.6%
서비스 2380
23.8%
여가생활 1198
 
12.0%
카페 576
 
5.8%
기타 82
 
0.8%

Length

2023-10-09T20:59:57.009522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-09T20:59:57.194090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식 5764
57.6%
서비스 2380
23.8%
여가생활 1198
 
12.0%
카페 576
 
5.8%
기타 82
 
0.8%

gugun_cd
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)0.8%
Missing675
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean176.77619
Minimum31
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:57.414085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile41
Q192
median178
Q3261
95-th percentile373
Maximum376
Range345
Interquartile range (IQR)169

Descriptive statistics

Standard deviation103.57778
Coefficient of variation (CV)0.58592606
Kurtosis-0.97492994
Mean176.77619
Median Absolute Deviation (MAD)86
Skewness0.38446241
Sum1648438
Variance10728.356
MonotonicityNot monotonic
2023-10-09T20:59:57.686355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189 810
 
8.1%
373 674
 
6.7%
48 662
 
6.6%
275 592
 
5.9%
216 478
 
4.8%
178 412
 
4.1%
92 412
 
4.1%
135 406
 
4.1%
41 386
 
3.9%
95 342
 
3.4%
Other values (65) 4151
41.5%
(Missing) 675
 
6.8%
ValueCountFrequency (%)
31 11
 
0.1%
39 23
 
0.2%
40 138
 
1.4%
41 386
3.9%
42 70
 
0.7%
45 9
 
0.1%
48 662
6.6%
53 109
 
1.1%
54 8
 
0.1%
56 4
 
< 0.1%
ValueCountFrequency (%)
376 9
 
0.1%
373 674
6.7%
372 5
 
0.1%
370 18
 
0.2%
369 69
 
0.7%
365 15
 
0.1%
350 4
 
< 0.1%
346 47
 
0.5%
344 7
 
0.1%
338 30
 
0.3%

gugun_nm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부산진구
831 
사상구
810 
북구
801 
해운대구
790 
동래구
771 
Other values (9)
5997 

Length

Max length4
Median length3
Mean length2.9558
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수영구
2nd row사하구
3rd row기장군
4th row북구
5th row남구

Common Values

ValueCountFrequency (%)
부산진구 831
 
8.3%
사상구 810
 
8.1%
북구 801
 
8.0%
해운대구 790
 
7.9%
동래구 771
 
7.7%
연제구 751
 
7.5%
사하구 707
 
7.1%
동구 694
 
6.9%
<NA> 675
 
6.8%
기장군 671
 
6.7%
Other values (4) 2499
25.0%

Length

2023-10-09T20:59:57.949270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산진구 831
 
8.3%
사상구 810
 
8.1%
북구 801
 
8.0%
해운대구 790
 
7.9%
동래구 771
 
7.7%
연제구 751
 
7.5%
사하구 707
 
7.1%
동구 694
 
6.9%
na 675
 
6.8%
기장군 671
 
6.7%
Other values (4) 2499
25.0%

unit
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.4849
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:58.138178image/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 deviation52.668421
Coefficient of variation (CV)3.0122232
Kurtosis7.3362916
Mean17.4849
Median Absolute Deviation (MAD)0
Skewness3.0007447
Sum174849
Variance2773.9626
MonotonicityNot monotonic
2023-10-09T20:59:58.342915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 9069
90.7%
200 648
 
6.5%
120 75
 
0.8%
130 71
 
0.7%
100 71
 
0.7%
150 35
 
0.4%
180 21
 
0.2%
170 3
 
< 0.1%
110 3
 
< 0.1%
140 2
 
< 0.1%
ValueCountFrequency (%)
1 9069
90.7%
100 71
 
0.7%
110 3
 
< 0.1%
120 75
 
0.8%
130 71
 
0.7%
140 2
 
< 0.1%
150 35
 
0.4%
170 3
 
< 0.1%
180 21
 
0.2%
200 648
 
6.5%
ValueCountFrequency (%)
350 2
 
< 0.1%
200 648
6.5%
180 21
 
0.2%
170 3
 
< 0.1%
150 35
 
0.4%
140 2
 
< 0.1%
130 71
 
0.7%
120 75
 
0.8%
110 3
 
< 0.1%
100 71
 
0.7%

unitprice
Real number (ℝ)

ZEROS 

Distinct239
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12711.582
Minimum0
Maximum266200
Zeros245
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-10-09T20:59:58.586764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1200
Q14500
median7000
Q313000
95-th percentile40000
Maximum266200
Range266200
Interquartile range (IQR)8500

Descriptive statistics

Standard deviation21296.986
Coefficient of variation (CV)1.6754001
Kurtosis38.492543
Mean12711.582
Median Absolute Deviation (MAD)3500
Skewness5.5677972
Sum1.2711582 × 108
Variance4.5356161 × 108
MonotonicityNot monotonic
2023-10-09T20:59:58.867413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000 855
 
8.6%
7000 756
 
7.6%
3000 610
 
6.1%
5000 540
 
5.4%
15000 509
 
5.1%
10000 449
 
4.5%
9000 422
 
4.2%
8000 362
 
3.6%
12000 268
 
2.7%
4500 252
 
2.5%
Other values (229) 4977
49.8%
ValueCountFrequency (%)
0 245
2.5%
200 7
 
0.1%
250 2
 
< 0.1%
300 9
 
0.1%
350 2
 
< 0.1%
450 2
 
< 0.1%
500 17
 
0.2%
800 9
 
0.1%
1000 82
 
0.8%
1200 175
1.8%
ValueCountFrequency (%)
266200 2
 
< 0.1%
229900 1
 
< 0.1%
210000 8
0.1%
205700 1
 
< 0.1%
200000 12
0.1%
190000 16
0.2%
187550 1
 
< 0.1%
183000 2
 
< 0.1%
181500 1
 
< 0.1%
180000 2
 
< 0.1%

prices
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

rm
Text

MISSING 

Distinct122
Distinct (%)15.5%
Missing9213
Missing (%)92.1%
Memory size156.2 KiB
2023-10-09T20:59:59.370216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length19
Mean length7.7814485
Min length1

Characters and Unicode

Total characters6124
Distinct characters205
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

Unique25 ?
Unique (%)3.2%

Sample

1st row노래연습장
2nd row모듬곰탕
3rd row착한업소
4th row슈프림
5th row300원/10분
ValueCountFrequency (%)
비회원 30
 
2.7%
1300 30
 
2.7%
초급 28
 
2.5%
남 28
 
2.5%
월 28
 
2.5%
주말 26
 
2.3%
50000 25
 
2.2%
이용료 25
 
2.2%
주말30000 24
 
2.1%
아메리카노 24
 
2.1%
Other values (124) 851
76.1%
2023-10-09T21:00:00.375384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 972
 
15.9%
428
 
7.0%
1 241
 
3.9%
원 235
 
3.8%
2 151
 
2.5%
3 142
 
2.3%
/ 142
 
2.3%
5 112
 
1.8%
시 98
 
1.6%
이 93
 
1.5%
Other values (195) 3510
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3472
56.7%
Decimal Number 1759
28.7%
Space Separator 428
 
7.0%
Other Punctuation 262
 
4.3%
Lowercase Letter 118
 
1.9%
Close Punctuation 28
 
0.5%
Open Punctuation 28
 
0.5%
Math Symbol 17
 
0.3%
Uppercase Letter 12
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 235
 
6.8%
시 98
 
2.8%
이 93
 
2.7%
주 89
 
2.6%
업 85
 
2.4%
분 81
 
2.3%
말 72
 
2.1%
회 68
 
2.0%
료 68
 
2.0%
기 56
 
1.6%
Other values (170) 2527
72.8%
Decimal Number
ValueCountFrequency (%)
0 972
55.3%
1 241
 
13.7%
2 151
 
8.6%
3 142
 
8.1%
5 112
 
6.4%
4 55
 
3.1%
9 37
 
2.1%
6 21
 
1.2%
8 15
 
0.9%
7 13
 
0.7%
Other Punctuation
ValueCountFrequency (%)
/ 142
54.2%
, 81
30.9%
: 21
 
8.0%
* 11
 
4.2%
. 6
 
2.3%
% 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
g 66
55.9%
k 30
25.4%
m 11
 
9.3%
c 11
 
9.3%
Space Separator
ValueCountFrequency (%)
428
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3451
56.4%
Common 2522
41.2%
Latin 130
 
2.1%
Han 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 235
 
6.8%
시 98
 
2.8%
이 93
 
2.7%
주 89
 
2.6%
업 85
 
2.5%
분 81
 
2.3%
말 72
 
2.1%
회 68
 
2.0%
료 68
 
2.0%
기 56
 
1.6%
Other values (168) 2506
72.6%
Common
ValueCountFrequency (%)
0 972
38.5%
428
17.0%
1 241
 
9.6%
2 151
 
6.0%
3 142
 
5.6%
/ 142
 
5.6%
5 112
 
4.4%
, 81
 
3.2%
4 55
 
2.2%
9 37
 
1.5%
Other values (10) 161
 
6.4%
Latin
ValueCountFrequency (%)
g 66
50.8%
k 30
23.1%
R 12
 
9.2%
m 11
 
8.5%
c 11
 
8.5%
Han
ValueCountFrequency (%)
大 12
57.1%
小 9
42.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3451
56.4%
ASCII 2652
43.3%
CJK 21
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 972
36.7%
428
16.1%
1 241
 
9.1%
2 151
 
5.7%
3 142
 
5.4%
/ 142
 
5.4%
5 112
 
4.2%
, 81
 
3.1%
g 66
 
2.5%
4 55
 
2.1%
Other values (15) 262
 
9.9%
Hangul
ValueCountFrequency (%)
원 235
 
6.8%
시 98
 
2.8%
이 93
 
2.7%
주 89
 
2.6%
업 85
 
2.5%
분 81
 
2.3%
말 72
 
2.1%
회 68
 
2.0%
료 68
 
2.0%
기 56
 
1.6%
Other values (168) 2506
72.6%
CJK
ValueCountFrequency (%)
大 12
57.1%
小 9
42.9%

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 

Distinct721
Distinct (%)7.7%
Missing618
Missing (%)6.2%
Memory size156.2 KiB
2023-10-09T21:00:00.890663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.036026
Min length10

Characters and Unicode

Total characters112922
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

Unique8 ?
Unique (%)0.1%

Sample

1st row051-611-7412
2nd row051-201-2331
3rd row051-728-5754
4th row051-332-7848
5th row051-622-2234
ValueCountFrequency (%)
051-000-0000 93
 
1.0%
051-559-1592 75
 
0.8%
051-611-5727 62
 
0.7%
051-622-2234 60
 
0.6%
051-612-3808 51
 
0.5%
051-326-2747 46
 
0.5%
051-462-5501 45
 
0.5%
051-627-5986 44
 
0.5%
051-469-2377 43
 
0.5%
051-626-3332 42
 
0.4%
Other values (711) 8821
94.0%
2023-10-09T21:00:01.780236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 18356
16.3%
0 18107
16.0%
5 16639
14.7%
1 14812
13.1%
2 8705
7.7%
7 7307
 
6.5%
3 6746
 
6.0%
8 6456
 
5.7%
6 6185
 
5.5%
4 5604
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94566
83.7%
Dash Punctuation 18356
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18107
19.1%
5 16639
17.6%
1 14812
15.7%
2 8705
9.2%
7 7307
7.7%
3 6746
 
7.1%
8 6456
 
6.8%
6 6185
 
6.5%
4 5604
 
5.9%
9 4005
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 18356
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 112922
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 18356
16.3%
0 18107
16.0%
5 16639
14.7%
1 14812
13.1%
2 8705
7.7%
7 7307
 
6.5%
3 6746
 
6.0%
8 6456
 
5.7%
6 6185
 
5.5%
4 5604
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 18356
16.3%
0 18107
16.0%
5 16639
14.7%
1 14812
13.1%
2 8705
7.7%
7 7307
 
6.5%
3 6746
 
6.0%
8 6456
 
5.7%
6 6185
 
5.5%
4 5604
 
5.0%

parkng_at
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
6182 
Y
3200 
 
618

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6182
61.8%
Y 3200
32.0%
618
 
6.2%

Length

2023-10-09T21:00:02.061375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-09T21:00:02.237427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6182
65.9%
y 3200
34.1%

card_at
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
8466 
N
916 
 
618

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 8466
84.7%
N 916
 
9.2%
618
 
6.2%

Length

2023-10-09T21:00:02.449170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-09T21:00:02.650533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 8466
90.2%
n 916
 
9.8%

item_name
Categorical

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
돼지갈비(외식)
 
334
커피
 
318
삼겹살(외식)
 
316
탕수육
 
305
PC방 이용료
 
301
Other values (40)
8426 

Length

Max length8
Median length6
Mean length4.266
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국산차
2nd row칼국수
3rd row미용료
4th row목욕료
5th row김밥

Common Values

ValueCountFrequency (%)
돼지갈비(외식) 334
 
3.3%
커피 318
 
3.2%
삼겹살(외식) 316
 
3.2%
탕수육 305
 
3.0%
PC방 이용료 301
 
3.0%
짬뽕 301
 
3.0%
자장면 299
 
3.0%
양복세탁료 299
 
3.0%
미용료 287
 
2.9%
당구장이용료 282
 
2.8%
Other values (35) 6958
69.6%

Length

2023-10-09T21:00:02.895252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용료 793
 
7.5%
돼지갈비(외식 334
 
3.2%
커피 318
 
3.0%
삼겹살(외식 316
 
3.0%
탕수육 305
 
2.9%
pc방 301
 
2.9%
짬뽕 301
 
2.9%
자장면 299
 
2.8%
양복세탁료 299
 
2.8%
미용료 287
 
2.7%
Other values (35) 6995
66.3%

last_load_dttm
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-09-01 06:17:08
1398 
2023-09-01 06:17:11
1305 
2023-09-01 06:17:05
1286 
2023-09-01 06:17:14
1282 
2023-09-01 06:17:07
967 
Other values (6)
3762 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-01 06:17:14
2nd row2023-09-01 06:17:12
3rd row2023-09-01 06:17:05
4th row2023-09-01 06:17:09
5th row2023-09-01 06:17:14

Common Values

ValueCountFrequency (%)
2023-09-01 06:17:08 1398
14.0%
2023-09-01 06:17:11 1305
13.1%
2023-09-01 06:17:05 1286
12.9%
2023-09-01 06:17:14 1282
12.8%
2023-09-01 06:17:07 967
9.7%
2023-09-01 06:17:12 858
8.6%
2023-09-01 06:17:10 858
8.6%
2023-09-01 06:17:09 772
7.7%
2023-09-01 06:17:13 708
7.1%
2023-09-01 06:17:06 518
 
5.2%

Length

2023-10-09T21:00:03.171953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-09-01 10000
50.0%
06:17:08 1398
 
7.0%
06:17:11 1305
 
6.5%
06:17:05 1286
 
6.4%
06:17:14 1282
 
6.4%
06:17:07 967
 
4.8%
06:17:12 858
 
4.3%
06:17:10 858
 
4.3%
06:17:09 772
 
3.9%
06:17:13 708
 
3.5%
Other values (2) 566
 
2.8%

Sample

skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
6513821370713112930315054175054171294192020-09-15455카페261수영구13000<NA><NA><NA><NA><NA><NA>051-611-7412NN국산차2023-09-01 06:17:14
5168022712513413217914645914645911324192018-10-30454외식216사하구15000<NA><NA><NA><NA><NA><NA>051-201-2331NY칼국수2023-09-01 06:17:12
160827722512812628764679884679881264192018-12-26466서비스48기장군115000<NA><NA><NA><NA><NA><NA>051-728-5754YY미용료2023-09-01 06:17:05
3155624724712712516575313425313421254192021-11-16466서비스178북구17000<NA><NA><NA><NA><NA><NA>051-332-7848NY목욕료2023-09-01 06:17:09
6584921299413313126935025105025101314192020-08-04454외식53남구12000<NA><NA><NA><NA><NA><NA>051-622-2234YY김밥2023-09-01 06:17:14
5186322692014414219034644434644431424192018-10-30454외식254수영구13050769<NA><NA><NA><NA><NA><NA>051-759-1717NY등심구이2023-09-01 06:17:12
4568323309413813629645210055210051364192021-06-01454외식189사상구117700<NA><NA><NA><NA><NA><NA>051-322-7404YY치킨2023-09-01 06:17:11
5341122541812412216184638064638061224192018-10-16465여가생활176북구17200<NA><NA><NA><NA><NA><NA>051-338-0096NY당구장이용료2023-09-01 06:17:12
1219126668214113924435036705036701394192020-08-18454외식95동래구14500<NA><NA><NA><NA><NA><NA>051-555-7377YY자장면2023-09-01 06:17:06
5944521932412712511785088395088391254192020-11-10466서비스59남구17000<NA><NA><NA><NA><NA><NA>051-627-8800NY목욕료2023-09-01 06:17:13
skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
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