Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells62527
Missing cells (%)24.0%
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 (50.7%)Imbalance
card_at is highly imbalanced (56.6%)Imbalance
bssh_no has 1077 (10.8%) missing valuesMissing
gugun_cd has 1079 (10.8%) missing valuesMissing
prices has 10000 (100.0%) missing valuesMissing
rm has 9294 (92.9%) 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 1077 (10.8%) 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 581 (5.8%) zerosZeros

Reproduction

Analysis started2024-04-17 10:03:47.338891
Analysis finished2024-04-17 10:03:47.852716
Duration0.51 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%
Mean83181.715
Minimum47934
Maximum118532
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:47.911052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47934
5-th percentile51530.7
Q165865.5
median83041
Q3100614
95-th percentile114816
Maximum118532
Range70598
Interquartile range (IQR)34748.5

Descriptive statistics

Standard deviation20270.934
Coefficient of variation (CV)0.24369459
Kurtosis-1.1919121
Mean83181.715
Median Absolute Deviation (MAD)17349.5
Skewness-7.8355196 × 10-5
Sum8.3181715 × 108
Variance4.1091076 × 108
MonotonicityNot monotonic
2024-04-17T19:03:48.038059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63650 1
 
< 0.1%
54913 1
 
< 0.1%
103080 1
 
< 0.1%
83250 1
 
< 0.1%
50989 1
 
< 0.1%
106865 1
 
< 0.1%
116636 1
 
< 0.1%
77484 1
 
< 0.1%
72737 1
 
< 0.1%
104078 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
47934 1
< 0.1%
47942 1
< 0.1%
47943 1
< 0.1%
47951 1
< 0.1%
47976 1
< 0.1%
47981 1
< 0.1%
47982 1
< 0.1%
47988 1
< 0.1%
47994 1
< 0.1%
48016 1
< 0.1%
ValueCountFrequency (%)
118532 1
< 0.1%
118514 1
< 0.1%
118511 1
< 0.1%
118509 1
< 0.1%
118505 1
< 0.1%
118498 1
< 0.1%
118494 1
< 0.1%
118491 1
< 0.1%
118461 1
< 0.1%
118454 1
< 0.1%

ccode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.4369
Minimum108
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:48.169042image/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 deviation11.577488
Coefficient of variation (CV)0.086763764
Kurtosis-0.9063945
Mean133.4369
Median Absolute Deviation (MAD)9
Skewness-0.25329474
Sum1334369
Variance134.03822
MonotonicityNot monotonic
2024-04-17T19:03:48.287405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
125 326
 
3.3%
143 318
 
3.2%
142 315
 
3.1%
133 308
 
3.1%
134 307
 
3.1%
149 301
 
3.0%
141 298
 
3.0%
137 297
 
3.0%
123 295
 
2.9%
132 292
 
2.9%
Other values (35) 6943
69.4%
ValueCountFrequency (%)
108 66
 
0.7%
109 4
 
< 0.1%
110 95
0.9%
111 6
 
0.1%
112 205
2.1%
113 232
2.3%
114 212
2.1%
115 186
1.9%
116 161
1.6%
117 105
1.1%
ValueCountFrequency (%)
152 242
2.4%
151 288
2.9%
150 260
2.6%
149 301
3.0%
148 284
2.8%
147 261
2.6%
146 263
2.6%
145 145
1.5%
144 259
2.6%
143 318
3.2%

pcode
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.4369
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:48.405532image/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 deviation11.577488
Coefficient of variation (CV)0.088083999
Kurtosis-0.9063945
Mean131.4369
Median Absolute Deviation (MAD)9
Skewness-0.25329474
Sum1314369
Variance134.03822
MonotonicityNot monotonic
2024-04-17T19:03:48.520082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
123 326
 
3.3%
141 318
 
3.2%
140 315
 
3.1%
131 308
 
3.1%
132 307
 
3.1%
147 301
 
3.0%
139 298
 
3.0%
135 297
 
3.0%
121 295
 
2.9%
130 292
 
2.9%
Other values (35) 6943
69.4%
ValueCountFrequency (%)
106 66
 
0.7%
107 4
 
< 0.1%
108 95
0.9%
109 6
 
0.1%
110 205
2.1%
111 232
2.3%
112 212
2.1%
113 186
1.9%
114 161
1.6%
115 105
1.1%
ValueCountFrequency (%)
150 242
2.4%
149 288
2.9%
148 260
2.6%
147 301
3.0%
146 284
2.8%
145 261
2.6%
144 263
2.6%
143 145
1.5%
142 259
2.6%
141 318
3.2%

bssh_no
Real number (ℝ)

MISSING 

Distinct678
Distinct (%)7.6%
Missing1077
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean2135.7035
Minimum985
Maximum3199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:48.641748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum985
5-th percentile1041
Q11537
median2023
Q32790
95-th percentile3049.9
Maximum3199
Range2214
Interquartile range (IQR)1253

Descriptive statistics

Standard deviation679.52205
Coefficient of variation (CV)0.31817247
Kurtosis-1.3993667
Mean2135.7035
Median Absolute Deviation (MAD)665
Skewness-0.095460678
Sum19056882
Variance461750.22
MonotonicityNot monotonic
2024-04-17T19:03:48.777726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2693 61
 
0.6%
1798 59
 
0.6%
2690 58
 
0.6%
2982 54
 
0.5%
1650 54
 
0.5%
1766 50
 
0.5%
1140 49
 
0.5%
1055 47
 
0.5%
2002 45
 
0.4%
1320 44
 
0.4%
Other values (668) 8402
84.0%
(Missing) 1077
 
10.8%
ValueCountFrequency (%)
985 11
 
0.1%
986 14
0.1%
988 22
0.2%
991 9
 
0.1%
996 31
0.3%
997 13
0.1%
998 9
 
0.1%
999 9
 
0.1%
1004 29
0.3%
1012 11
 
0.1%
ValueCountFrequency (%)
3199 2
< 0.1%
3197 1
 
< 0.1%
3196 2
< 0.1%
3195 1
 
< 0.1%
3187 2
< 0.1%
3185 1
 
< 0.1%
3183 1
 
< 0.1%
3178 3
< 0.1%
3176 1
 
< 0.1%
3175 1
 
< 0.1%

search_no
Real number (ℝ)

Distinct8927
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean478650.33
Minimum456029
Maximum509102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:48.930691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456029
5-th percentile457837.9
Q1465938.25
median476101.5
Q3491895.25
95-th percentile504931.3
Maximum509102
Range53073
Interquartile range (IQR)25957

Descriptive statistics

Standard deviation15015.966
Coefficient of variation (CV)0.031371474
Kurtosis-1.1466018
Mean478650.33
Median Absolute Deviation (MAD)11821
Skewness0.31848343
Sum4.7865033 × 109
Variance2.2547924 × 108
MonotonicityNot monotonic
2024-04-17T19:03:49.072080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
479013 6
 
0.1%
465850 5
 
0.1%
467448 5
 
0.1%
463402 4
 
< 0.1%
463741 4
 
< 0.1%
463080 4
 
< 0.1%
459705 4
 
< 0.1%
465963 4
 
< 0.1%
505377 4
 
< 0.1%
468870 4
 
< 0.1%
Other values (8917) 9956
99.6%
ValueCountFrequency (%)
456029 2
< 0.1%
456032 2
< 0.1%
456036 1
< 0.1%
456037 1
< 0.1%
456039 1
< 0.1%
456041 1
< 0.1%
456042 1
< 0.1%
456045 1
< 0.1%
456050 1
< 0.1%
456052 1
< 0.1%
ValueCountFrequency (%)
509102 1
< 0.1%
509100 1
< 0.1%
509097 1
< 0.1%
509096 1
< 0.1%
509091 1
< 0.1%
509086 1
< 0.1%
509080 2
< 0.1%
509075 1
< 0.1%
509073 2
< 0.1%
509066 2
< 0.1%

prices_no
Real number (ℝ)

Distinct8927
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean478650.33
Minimum456029
Maximum509102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:49.212362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456029
5-th percentile457837.9
Q1465938.25
median476101.5
Q3491895.25
95-th percentile504931.3
Maximum509102
Range53073
Interquartile range (IQR)25957

Descriptive statistics

Standard deviation15015.966
Coefficient of variation (CV)0.031371474
Kurtosis-1.1466018
Mean478650.33
Median Absolute Deviation (MAD)11821
Skewness0.31848343
Sum4.7865033 × 109
Variance2.2547924 × 108
MonotonicityNot monotonic
2024-04-17T19:03:49.341704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
479013 6
 
0.1%
465850 5
 
0.1%
467448 5
 
0.1%
463402 4
 
< 0.1%
463741 4
 
< 0.1%
463080 4
 
< 0.1%
459705 4
 
< 0.1%
465963 4
 
< 0.1%
505377 4
 
< 0.1%
468870 4
 
< 0.1%
Other values (8917) 9956
99.6%
ValueCountFrequency (%)
456029 2
< 0.1%
456032 2
< 0.1%
456036 1
< 0.1%
456037 1
< 0.1%
456039 1
< 0.1%
456041 1
< 0.1%
456042 1
< 0.1%
456045 1
< 0.1%
456050 1
< 0.1%
456052 1
< 0.1%
ValueCountFrequency (%)
509102 1
< 0.1%
509100 1
< 0.1%
509097 1
< 0.1%
509096 1
< 0.1%
509091 1
< 0.1%
509086 1
< 0.1%
509080 2
< 0.1%
509075 1
< 0.1%
509073 2
< 0.1%
509066 2
< 0.1%

prdlst
Real number (ℝ)

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.4369
Minimum106
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:49.499339image/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 deviation11.577488
Coefficient of variation (CV)0.088083999
Kurtosis-0.9063945
Mean131.4369
Median Absolute Deviation (MAD)9
Skewness-0.25329474
Sum1314369
Variance134.03822
MonotonicityNot monotonic
2024-04-17T19:03:49.620546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
123 326
 
3.3%
141 318
 
3.2%
140 315
 
3.1%
131 308
 
3.1%
132 307
 
3.1%
147 301
 
3.0%
139 298
 
3.0%
135 297
 
3.0%
121 295
 
2.9%
130 292
 
2.9%
Other values (35) 6943
69.4%
ValueCountFrequency (%)
106 66
 
0.7%
107 4
 
< 0.1%
108 95
0.9%
109 6
 
0.1%
110 205
2.1%
111 232
2.3%
112 212
2.1%
113 186
1.9%
114 161
1.6%
115 105
1.1%
ValueCountFrequency (%)
150 242
2.4%
149 288
2.9%
148 260
2.6%
147 301
3.0%
146 284
2.8%
145 261
2.6%
144 263
2.6%
143 145
1.5%
142 259
2.6%
141 318
3.2%

cl_no
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
419
8923 
<NA>
1077 

Length

Max length4
Median length3
Mean length3.1077
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
419 8923
89.2%
<NA> 1077
 
10.8%

Length

2024-04-17T19:03:49.730015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:49.808464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
419 8923
89.2%
na 1077
 
10.8%

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
2024-04-17T19:03:49.900709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:03:50.042040image/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
5912 
466
2335 
465
1144 
455
 
543
467
 
66

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
454 5912
59.1%
466 2335
 
23.4%
465 1144
 
11.4%
455 543
 
5.4%
467 66
 
0.7%

Length

2024-04-17T19:03:50.164870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:50.271496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
454 5912
59.1%
466 2335
 
23.4%
465 1144
 
11.4%
455 543
 
5.4%
467 66
 
0.7%

pum_nm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
외식
5912 
서비스
2335 
여가생활
1144 
카페
 
543
기타
 
66

Length

Max length4
Median length2
Mean length2.4623
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외식 5912
59.1%
서비스 2335
 
23.4%
여가생활 1144
 
11.4%
카페 543
 
5.4%
기타 66
 
0.7%

Length

2024-04-17T19:03:50.382403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:50.484162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식 5912
59.1%
서비스 2335
 
23.4%
여가생활 1144
 
11.4%
카페 543
 
5.4%
기타 66
 
0.7%

gugun_cd
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)0.8%
Missing1079
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean175.82614
Minimum31
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:50.600911image/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 deviation105.49633
Coefficient of variation (CV)0.60000369
Kurtosis-0.99049328
Mean175.82614
Median Absolute Deviation (MAD)85
Skewness0.40597045
Sum1568545
Variance11129.476
MonotonicityNot monotonic
2024-04-17T19:03:51.003489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
373 723
 
7.2%
189 673
 
6.7%
48 638
 
6.4%
275 571
 
5.7%
216 472
 
4.7%
41 470
 
4.7%
135 382
 
3.8%
178 371
 
3.7%
95 337
 
3.4%
92 321
 
3.2%
Other values (63) 3963
39.6%
(Missing) 1079
 
10.8%
ValueCountFrequency (%)
31 11
 
0.1%
39 18
 
0.2%
40 158
 
1.6%
41 470
4.7%
42 28
 
0.3%
45 7
 
0.1%
48 638
6.4%
53 115
 
1.1%
54 28
 
0.3%
57 318
3.2%
ValueCountFrequency (%)
376 4
 
< 0.1%
373 723
7.2%
372 7
 
0.1%
370 20
 
0.2%
369 63
 
0.6%
365 14
 
0.1%
350 11
 
0.1%
346 59
 
0.6%
345 5
 
0.1%
344 10
 
0.1%

gugun_nm
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
1079 
해운대구
831 
동래구
796 
북구
780 
부산진구
750 
Other values (9)
5764 

Length

Max length4
Median length3
Mean length3.0109
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동구
2nd row연제구
3rd row수영구
4th row중구
5th row동래구

Common Values

ValueCountFrequency (%)
<NA> 1079
10.8%
해운대구 831
 
8.3%
동래구 796
 
8.0%
북구 780
 
7.8%
부산진구 750
 
7.5%
연제구 707
 
7.1%
금정구 685
 
6.9%
사하구 674
 
6.7%
사상구 673
 
6.7%
남구 655
 
6.6%
Other values (4) 2370
23.7%

Length

2024-04-17T19:03:51.132205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1079
10.8%
해운대구 831
 
8.3%
동래구 796
 
8.0%
북구 780
 
7.8%
부산진구 750
 
7.5%
연제구 707
 
7.1%
금정구 685
 
6.9%
사하구 674
 
6.7%
사상구 673
 
6.7%
남구 655
 
6.6%
Other values (4) 2370
23.7%

unit
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.7191
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:51.237010image/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 deviation55.033719
Coefficient of variation (CV)2.9399768
Kurtosis7.0075024
Mean18.7191
Median Absolute Deviation (MAD)0
Skewness2.918697
Sum187191
Variance3028.7103
MonotonicityNot monotonic
2024-04-17T19:03:51.326723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 9021
90.2%
200 700
 
7.0%
130 75
 
0.8%
120 75
 
0.8%
100 45
 
0.4%
150 30
 
0.3%
180 22
 
0.2%
170 10
 
0.1%
350 9
 
0.1%
110 7
 
0.1%
ValueCountFrequency (%)
1 9021
90.2%
100 45
 
0.4%
110 7
 
0.1%
120 75
 
0.8%
130 75
 
0.8%
140 6
 
0.1%
150 30
 
0.3%
170 10
 
0.1%
180 22
 
0.2%
200 700
 
7.0%
ValueCountFrequency (%)
350 9
 
0.1%
200 700
7.0%
180 22
 
0.2%
170 10
 
0.1%
150 30
 
0.3%
140 6
 
0.1%
130 75
 
0.8%
120 75
 
0.8%
110 7
 
0.1%
100 45
 
0.4%

unitprice
Real number (ℝ)

ZEROS 

Distinct208
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11864.515
Minimum0
Maximum326700
Zeros581
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:03:51.441644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13900
median7000
Q312800
95-th percentile40000
Maximum326700
Range326700
Interquartile range (IQR)8900

Descriptive statistics

Standard deviation20865.346
Coefficient of variation (CV)1.7586345
Kurtosis44.209366
Mean11864.515
Median Absolute Deviation (MAD)4000
Skewness5.9102182
Sum1.1864515 × 108
Variance4.3536266 × 108
MonotonicityNot monotonic
2024-04-17T19:03:51.595252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000 854
 
8.5%
5000 657
 
6.6%
7000 641
 
6.4%
3000 600
 
6.0%
0 581
 
5.8%
15000 496
 
5.0%
10000 452
 
4.5%
9000 397
 
4.0%
8000 313
 
3.1%
4000 269
 
2.7%
Other values (198) 4740
47.4%
ValueCountFrequency (%)
0 581
5.8%
35 1
 
< 0.1%
200 13
 
0.1%
250 11
 
0.1%
300 35
 
0.4%
350 23
 
0.2%
450 13
 
0.1%
500 28
 
0.3%
800 2
 
< 0.1%
1000 94
 
0.9%
ValueCountFrequency (%)
326700 1
 
< 0.1%
229900 1
 
< 0.1%
217800 2
 
< 0.1%
210000 8
0.1%
205700 4
 
< 0.1%
200000 10
0.1%
190000 15
0.1%
180000 6
 
0.1%
179000 3
 
< 0.1%
170400 1
 
< 0.1%

prices
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

rm
Text

MISSING 

Distinct100
Distinct (%)14.2%
Missing9294
Missing (%)92.9%
Memory size156.2 KiB
2024-04-17T19:03:51.841625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length7.3116147
Min length1

Characters and Unicode

Total characters5162
Distinct characters188
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

Unique15 ?
Unique (%)2.1%

Sample

1st row인상
2nd row성인
3rd row미스트피자콤보 R
4th row페업
5th row재개발지역으로페업
ValueCountFrequency (%)
비회원 43
 
4.7%
1300 43
 
4.7%
재개발지역으로페업 28
 
3.1%
아메리카노 26
 
2.8%
주말 25
 
2.7%
10분 23
 
2.5%
인상 23
 
2.5%
50000 22
 
2.4%
페업 21
 
2.3%
주말30000 21
 
2.3%
Other values (103) 642
70.0%
2024-04-17T19:03:52.227015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 857
 
16.6%
301
 
5.8%
1 209
 
4.0%
원 187
 
3.6%
3 116
 
2.2%
2 102
 
2.0%
/ 102
 
2.0%
업 87
 
1.7%
주 77
 
1.5%
페 77
 
1.5%
Other values (178) 3047
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3034
58.8%
Decimal Number 1482
28.7%
Space Separator 301
 
5.8%
Other Punctuation 176
 
3.4%
Lowercase Letter 87
 
1.7%
Open Punctuation 27
 
0.5%
Close Punctuation 27
 
0.5%
Uppercase Letter 15
 
0.3%
Math Symbol 13
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 187
 
6.2%
업 87
 
2.9%
주 77
 
2.5%
페 77
 
2.5%
인 74
 
2.4%
지 61
 
2.0%
개 61
 
2.0%
이 57
 
1.9%
로 56
 
1.8%
말 54
 
1.8%
Other values (153) 2243
73.9%
Decimal Number
ValueCountFrequency (%)
0 857
57.8%
1 209
 
14.1%
3 116
 
7.8%
2 102
 
6.9%
5 72
 
4.9%
4 48
 
3.2%
9 48
 
3.2%
7 13
 
0.9%
6 12
 
0.8%
8 5
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 102
58.0%
, 48
27.3%
: 17
 
9.7%
* 5
 
2.8%
. 3
 
1.7%
% 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
g 60
69.0%
k 17
 
19.5%
c 5
 
5.7%
m 5
 
5.7%
Space Separator
ValueCountFrequency (%)
301
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3017
58.4%
Common 2026
39.2%
Latin 102
 
2.0%
Han 17
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 187
 
6.2%
업 87
 
2.9%
주 77
 
2.6%
페 77
 
2.6%
인 74
 
2.5%
지 61
 
2.0%
개 61
 
2.0%
이 57
 
1.9%
로 56
 
1.9%
말 54
 
1.8%
Other values (151) 2226
73.8%
Common
ValueCountFrequency (%)
0 857
42.3%
301
 
14.9%
1 209
 
10.3%
3 116
 
5.7%
2 102
 
5.0%
/ 102
 
5.0%
5 72
 
3.6%
4 48
 
2.4%
, 48
 
2.4%
9 48
 
2.4%
Other values (10) 123
 
6.1%
Latin
ValueCountFrequency (%)
g 60
58.8%
k 17
 
16.7%
R 15
 
14.7%
c 5
 
4.9%
m 5
 
4.9%
Han
ValueCountFrequency (%)
大 11
64.7%
小 6
35.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3017
58.4%
ASCII 2128
41.2%
CJK 17
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 857
40.3%
301
 
14.1%
1 209
 
9.8%
3 116
 
5.5%
2 102
 
4.8%
/ 102
 
4.8%
5 72
 
3.4%
g 60
 
2.8%
4 48
 
2.3%
, 48
 
2.3%
Other values (15) 213
 
10.0%
Hangul
ValueCountFrequency (%)
원 187
 
6.2%
업 87
 
2.9%
주 77
 
2.6%
페 77
 
2.6%
인 74
 
2.5%
지 61
 
2.0%
개 61
 
2.0%
이 57
 
1.9%
로 56
 
1.9%
말 54
 
1.8%
Other values (151) 2226
73.8%
CJK
ValueCountFrequency (%)
大 11
64.7%
小 6
35.3%

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 

Distinct671
Distinct (%)7.5%
Missing1077
Missing (%)10.8%
Memory size156.2 KiB
2024-04-17T19:03:52.465646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.02869
Min length10

Characters and Unicode

Total characters107332
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

Unique17 ?
Unique (%)0.2%

Sample

1st row051-468-4052
2nd row051-853-9298
3rd row051-626-3332
4th row051-254-1871
5th row051-555-3669
ValueCountFrequency (%)
051-622-2234 61
 
0.7%
051-207-1472 59
 
0.7%
051-727-7644 58
 
0.7%
051-332-0551 54
 
0.6%
051-612-3808 54
 
0.6%
051-326-2747 50
 
0.6%
051-611-5727 49
 
0.5%
051-559-1592 47
 
0.5%
051-513-2266 47
 
0.5%
051-866-9612 45
 
0.5%
Other values (661) 8399
94.1%
2024-04-17T19:03:52.882258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17496
16.3%
0 16701
15.6%
5 16111
15.0%
1 14077
13.1%
2 8588
8.0%
7 6853
 
6.4%
3 6490
 
6.0%
8 6163
 
5.7%
6 5926
 
5.5%
4 5371
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89836
83.7%
Dash Punctuation 17496
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16701
18.6%
5 16111
17.9%
1 14077
15.7%
2 8588
9.6%
7 6853
7.6%
3 6490
 
7.2%
8 6163
 
6.9%
6 5926
 
6.6%
4 5371
 
6.0%
9 3556
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 17496
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17496
16.3%
0 16701
15.6%
5 16111
15.0%
1 14077
13.1%
2 8588
8.0%
7 6853
 
6.4%
3 6490
 
6.0%
8 6163
 
5.7%
6 5926
 
5.5%
4 5371
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17496
16.3%
0 16701
15.6%
5 16111
15.0%
1 14077
13.1%
2 8588
8.0%
7 6853
 
6.4%
3 6490
 
6.0%
8 6163
 
5.7%
6 5926
 
5.5%
4 5371
 
5.0%

parkng_at
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
6093 
Y
2830 
732 
<NA>
 
345

Length

Max length4
Median length1
Mean length1.1035
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6093
60.9%
Y 2830
28.3%
732
 
7.3%
<NA> 345
 
3.5%

Length

2024-04-17T19:03:53.024853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:53.121608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6093
65.7%
y 2830
30.5%
na 345
 
3.7%

card_at
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Y
8426 
 
732
N
 
497
<NA>
 
345

Length

Max length4
Median length1
Mean length1.1035
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 8426
84.3%
732
 
7.3%
N 497
 
5.0%
<NA> 345
 
3.5%

Length

2024-04-17T19:03:53.222920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:03:53.312825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 8426
90.9%
n 497
 
5.4%
na 345
 
3.7%

item_name
Categorical

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
양복세탁료
 
326
돼지갈비(외식)
 
318
삼겹살(외식)
 
315
김밥
 
308
칼국수
 
307
Other values (41)
8426 

Length

Max length8
Median length7
Mean length4.1728
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의복수선료
2nd row치킨
3rd row짬뽕
4th row돼지갈비(외식)
5th row칼국수

Common Values

ValueCountFrequency (%)
양복세탁료 326
 
3.3%
돼지갈비(외식) 318
 
3.2%
삼겹살(외식) 315
 
3.1%
김밥 308
 
3.1%
칼국수 307
 
3.1%
갈비탕 301
 
3.0%
자장면 298
 
3.0%
짬뽕 297
 
3.0%
노래방이용료 295
 
2.9%
커피 292
 
2.9%
Other values (36) 6943
69.4%

Length

2024-04-17T19:03:53.410389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용료 613
 
5.9%
양복세탁료 326
 
3.2%
돼지갈비(외식 318
 
3.1%
삼겹살(외식 315
 
3.0%
김밥 308
 
3.0%
칼국수 307
 
3.0%
갈비탕 301
 
2.9%
자장면 298
 
2.9%
짬뽕 297
 
2.9%
노래방이용료 295
 
2.9%
Other values (36) 6965
67.3%

last_load_dttm
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-12-22 16:28:48
1251 
2020-12-22 16:28:51
1161 
2020-12-22 16:28:54
1134 
2020-12-22 16:28:56
905 
2020-12-22 16:28:53
896 
Other values (7)
4653 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-22 16:28:51
2nd row2020-12-22 16:28:47
3rd row2020-12-22 16:28:55
4th row2020-12-22 16:28:52
5th row2020-12-22 16:28:51

Common Values

ValueCountFrequency (%)
2020-12-22 16:28:48 1251
12.5%
2020-12-22 16:28:51 1161
11.6%
2020-12-22 16:28:54 1134
11.3%
2020-12-22 16:28:56 905
9.0%
2020-12-22 16:28:53 896
9.0%
2020-12-22 16:28:50 894
8.9%
2020-12-22 16:28:52 773
7.7%
2020-12-22 16:28:46 751
7.5%
2020-12-22 16:28:55 748
7.5%
2020-12-22 16:28:49 703
7.0%
Other values (2) 784
7.8%

Length

2024-04-17T19:03:53.529570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-22 10000
50.0%
16:28:48 1251
 
6.3%
16:28:51 1161
 
5.8%
16:28:54 1134
 
5.7%
16:28:56 905
 
4.5%
16:28:53 896
 
4.5%
16:28:50 894
 
4.5%
16:28:52 773
 
3.9%
16:28:46 751
 
3.8%
16:28:55 748
 
3.7%
Other values (3) 1487
 
7.4%

Sample

skeyccodepcodebssh_nosearch_noprices_noprdlstcl_noexamin_depum_cdpum_nmgugun_cdgugun_nmunitunitpricepricesrmbssh_nmlaloadrestelnoparkng_atcard_atitem_namelast_load_dttm
346126365011311112734697104697101114192019-01-22466서비스89동구15000<NA><NA><NA><NA><NA><NA>051-468-4052NN의복수선료2020-12-22 16:28:51
65459169313813619884932214932211364192020-03-03454외식275연제구117000<NA><NA><NA><NA><NA><NA>051-853-9298NY치킨2020-12-22 16:28:47
6115810909013713527334658504658501354192018-11-27454외식259수영구16000<NA><NA><NA><NA><NA><NA>051-626-3332YY짬뽕2020-12-22 16:28:55
414135681214314122504660314660311414192018-11-13454외식338중구2009000<NA><NA><NA><NA><NA><NA>051-254-1871NY돼지갈비(외식)2020-12-22 16:28:52
307906742413413213624749654749651324192019-04-30454외식104동래구13000<NA><NA><NA><NA><NA><NA>051-555-3669NY칼국수2020-12-22 16:28:51
513749930711611429615016475016471144192020-07-21466서비스373해운대구113000<NA><NA><NA><NA><NA><NA>051-701-1555YY사진(반명함판)2020-12-22 16:28:54
1558382667129127<NA>486877486877127<NA>2019-11-12466서비스<NA><NA>112000<NA><NA><NA><NA><NA><NA><NA>이용료2020-12-22 16:28:48
216197658414214010554811444811441404192019-08-06454외식41금정구2007500<NA><NA><NA><NA><NA><NA>051-513-2266NY삼겹살(외식)2020-12-22 16:28:49
5563210356511811624785068025068021164192020-10-13465여가생활373해운대구1200000<NA><NA><NA><NA><NA><NA>051-703-4007YY골프연습장2020-12-22 16:28:54
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