Overview

Dataset statistics

Number of variables12
Number of observations155
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory103.9 B

Variable types

Numeric5
Categorical7

Alerts

UPPER_CTGRY_NM has constant value ""Constant
LWPRT_CTGRY_NM has constant value ""Constant
AREA_NM has constant value ""Constant
TRRSRT_LO is highly overall correlated with SEQ_NO and 3 other fieldsHigh correlation
TRRSRT_LA is highly overall correlated with SEQ_NO and 3 other fieldsHigh correlation
AREA_ADDR is highly overall correlated with SEQ_NO and 3 other fieldsHigh correlation
SRCHWRD_NM is highly overall correlated with SEQ_NO and 3 other fieldsHigh correlation
SEQ_NO is highly overall correlated with SRCHWRD_NM and 3 other fieldsHigh correlation
PC_SCCNT_VALUE is highly overall correlated with SCCNT_SM_VALUE and 1 other fieldsHigh correlation
SCCNT_SM_VALUE is highly overall correlated with PC_SCCNT_VALUE and 1 other fieldsHigh correlation
SCCNT_DE is highly overall correlated with PC_SCCNT_VALUE and 1 other fieldsHigh correlation
SEQ_NO has unique valuesUnique
MOBILE_SCCNT_VALUE has 3 (1.9%) zerosZeros

Reproduction

Analysis started2023-12-10 09:59:33.663045
Analysis finished2023-12-10 09:59:41.342977
Duration7.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SEQ_NO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23367.4
Minimum2044
Maximum46021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-10T18:59:41.517156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2044
5-th percentile2051.7
Q117961.5
median23114
Q327696.5
95-th percentile46013.3
Maximum46021
Range43977
Interquartile range (IQR)9735

Descriptive statistics

Standard deviation14290.031
Coefficient of variation (CV)0.61153706
Kurtosis-0.70023842
Mean23367.4
Median Absolute Deviation (MAD)5145
Skewness0.12933965
Sum3621947
Variance2.0420499 × 108
MonotonicityNot monotonic
2023-12-10T18:59:41.863521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27674 1
 
0.6%
46012 1
 
0.6%
46011 1
 
0.6%
27694 1
 
0.6%
2064 1
 
0.6%
17974 1
 
0.6%
23119 1
 
0.6%
2065 1
 
0.6%
23120 1
 
0.6%
17975 1
 
0.6%
Other values (145) 145
93.5%
ValueCountFrequency (%)
2044 1
0.6%
2045 1
0.6%
2046 1
0.6%
2047 1
0.6%
2048 1
0.6%
2049 1
0.6%
2050 1
0.6%
2051 1
0.6%
2052 1
0.6%
2053 1
0.6%
ValueCountFrequency (%)
46021 1
0.6%
46020 1
0.6%
46019 1
0.6%
46018 1
0.6%
46017 1
0.6%
46016 1
0.6%
46015 1
0.6%
46014 1
0.6%
46013 1
0.6%
46012 1
0.6%

SRCHWRD_NM
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
한라산백록담
31 
관음사
31 
퍼시픽리솜
31 
쇠소깍
31 
곽지해수욕장
31 

Length

Max length6
Median length5
Mean length4.6
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한라산백록담
2nd row관음사
3rd row퍼시픽리솜
4th row쇠소깍
5th row곽지해수욕장

Common Values

ValueCountFrequency (%)
한라산백록담 31
20.0%
관음사 31
20.0%
퍼시픽리솜 31
20.0%
쇠소깍 31
20.0%
곽지해수욕장 31
20.0%

Length

2023-12-10T18:59:42.103556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:42.335571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한라산백록담 31
20.0%
관음사 31
20.0%
퍼시픽리솜 31
20.0%
쇠소깍 31
20.0%
곽지해수욕장 31
20.0%

UPPER_CTGRY_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
여행
155 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여행 155
100.0%

Length

2023-12-10T18:59:42.710749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:42.996378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여행 155
100.0%

LWPRT_CTGRY_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
관광지
155 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 155
100.0%

Length

2023-12-10T18:59:43.212736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:43.403664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 155
100.0%

MOBILE_SCCNT_VALUE
Real number (ℝ)

ZEROS 

Distinct65
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.167742
Minimum0
Maximum267
Zeros3
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-10T18:59:43.613832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.7
Q116
median28
Q338.5
95-th percentile88.9
Maximum267
Range267
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation29.809312
Coefficient of variation (CV)0.8724402
Kurtosis23.845396
Mean34.167742
Median Absolute Deviation (MAD)12
Skewness3.7437427
Sum5296
Variance888.59506
MonotonicityNot monotonic
2023-12-10T18:59:43.923882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 7
 
4.5%
14 7
 
4.5%
35 6
 
3.9%
15 6
 
3.9%
27 6
 
3.9%
16 5
 
3.2%
50 5
 
3.2%
32 4
 
2.6%
29 4
 
2.6%
34 4
 
2.6%
Other values (55) 101
65.2%
ValueCountFrequency (%)
0 3
1.9%
5 3
1.9%
7 1
 
0.6%
8 1
 
0.6%
9 2
 
1.3%
10 4
2.6%
11 3
1.9%
12 3
1.9%
13 3
1.9%
14 7
4.5%
ValueCountFrequency (%)
267 1
0.6%
116 1
0.6%
107 1
0.6%
104 1
0.6%
101 1
0.6%
98 1
0.6%
95 1
0.6%
91 1
0.6%
88 1
0.6%
84 1
0.6%

PC_SCCNT_VALUE
Real number (ℝ)

HIGH CORRELATION 

Distinct132
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean338.85161
Minimum75
Maximum2756
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-10T18:59:44.187592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile121.7
Q1202
median274
Q3403
95-th percentile625
Maximum2756
Range2681
Interquartile range (IQR)201

Descriptive statistics

Standard deviation273.42652
Coefficient of variation (CV)0.80692111
Kurtosis41.331393
Mean338.85161
Median Absolute Deviation (MAD)92
Skewness5.3273251
Sum52522
Variance74762.062
MonotonicityNot monotonic
2023-12-10T18:59:44.444712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 4
 
2.6%
376 3
 
1.9%
146 3
 
1.9%
140 3
 
1.9%
274 2
 
1.3%
182 2
 
1.3%
219 2
 
1.3%
192 2
 
1.3%
349 2
 
1.3%
241 2
 
1.3%
Other values (122) 130
83.9%
ValueCountFrequency (%)
75 1
0.6%
91 1
0.6%
104 1
0.6%
109 1
0.6%
111 1
0.6%
114 1
0.6%
118 1
0.6%
121 1
0.6%
122 1
0.6%
132 1
0.6%
ValueCountFrequency (%)
2756 1
0.6%
1411 1
0.6%
1360 1
0.6%
791 1
0.6%
746 1
0.6%
668 1
0.6%
647 1
0.6%
632 1
0.6%
622 2
1.3%
613 1
0.6%

SCCNT_SM_VALUE
Real number (ℝ)

HIGH CORRELATION 

Distinct135
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean373.01935
Minimum101
Maximum3023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-10T18:59:44.738420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile147.3
Q1227
median304
Q3447
95-th percentile639.4
Maximum3023
Range2922
Interquartile range (IQR)220

Descriptive statistics

Standard deviation292.80782
Coefficient of variation (CV)0.78496684
Kurtosis44.981317
Mean373.01935
Median Absolute Deviation (MAD)101
Skewness5.5671868
Sum57818
Variance85736.422
MonotonicityNot monotonic
2023-12-10T18:59:45.051300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
234 4
 
2.6%
284 2
 
1.3%
222 2
 
1.3%
620 2
 
1.3%
131 2
 
1.3%
438 2
 
1.3%
340 2
 
1.3%
173 2
 
1.3%
387 2
 
1.3%
626 2
 
1.3%
Other values (125) 133
85.8%
ValueCountFrequency (%)
101 1
0.6%
119 1
0.6%
123 1
0.6%
131 2
1.3%
133 1
0.6%
136 1
0.6%
141 1
0.6%
150 1
0.6%
155 1
0.6%
160 1
0.6%
ValueCountFrequency (%)
3023 1
0.6%
1486 1
0.6%
1427 1
0.6%
811 1
0.6%
770 1
0.6%
748 1
0.6%
679 1
0.6%
645 1
0.6%
637 1
0.6%
636 1
0.6%

SCCNT_DE
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210116
Minimum20210101
Maximum20210131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-10T18:59:45.335011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210101
5-th percentile20210102
Q120210108
median20210116
Q320210124
95-th percentile20210130
Maximum20210131
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.9732648
Coefficient of variation (CV)4.4399868 × 10-7
Kurtosis-1.2024794
Mean20210116
Median Absolute Deviation (MAD)8
Skewness0
Sum3.132568 × 109
Variance80.519481
MonotonicityIncreasing
2023-12-10T18:59:45.586748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210101 5
 
3.2%
20210102 5
 
3.2%
20210131 5
 
3.2%
20210130 5
 
3.2%
20210129 5
 
3.2%
20210128 5
 
3.2%
20210127 5
 
3.2%
20210126 5
 
3.2%
20210125 5
 
3.2%
20210124 5
 
3.2%
Other values (21) 105
67.7%
ValueCountFrequency (%)
20210101 5
3.2%
20210102 5
3.2%
20210103 5
3.2%
20210104 5
3.2%
20210105 5
3.2%
20210106 5
3.2%
20210107 5
3.2%
20210108 5
3.2%
20210109 5
3.2%
20210110 5
3.2%
ValueCountFrequency (%)
20210131 5
3.2%
20210130 5
3.2%
20210129 5
3.2%
20210128 5
3.2%
20210127 5
3.2%
20210126 5
3.2%
20210125 5
3.2%
20210124 5
3.2%
20210123 5
3.2%
20210122 5
3.2%

AREA_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
제주
155 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주 155
100.0%

Length

2023-12-10T18:59:45.838299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:46.075545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주 155
100.0%

AREA_ADDR
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
제주특별자치도 서귀포시 토평동
31 
제주특별자치도 제주시 산록북로 660(아라일동)
31 
제주특별자치도 서귀포시 중문관광로 154-17
31 
제주특별자치도 서귀포시 쇠소깍로 128(하효동)
31 
제주특별자치도 제주시 애월읍 금성5길
31 

Length

Max length29
Median length26
Mean length25
Min length20

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주특별자치도 서귀포시 토평동
2nd row제주특별자치도 제주시 산록북로 660(아라일동)
3rd row제주특별자치도 서귀포시 중문관광로 154-17
4th row제주특별자치도 서귀포시 쇠소깍로 128(하효동)
5th row제주특별자치도 제주시 애월읍 금성5길

Common Values

ValueCountFrequency (%)
제주특별자치도 서귀포시 토평동 31
20.0%
제주특별자치도 제주시 산록북로 660(아라일동) 31
20.0%
제주특별자치도 서귀포시 중문관광로 154-17 31
20.0%
제주특별자치도 서귀포시 쇠소깍로 128(하효동) 31
20.0%
제주특별자치도 제주시 애월읍 금성5길 31
20.0%

Length

2023-12-10T18:59:46.277016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:46.502245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주특별자치도 155
26.3%
서귀포시 93
15.8%
제주시 62
 
10.5%
토평동 31
 
5.3%
산록북로 31
 
5.3%
660(아라일동 31
 
5.3%
중문관광로 31
 
5.3%
154-17 31
 
5.3%
쇠소깍로 31
 
5.3%
128(하효동 31
 
5.3%
Other values (2) 62
 
10.5%

TRRSRT_LA
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
33.3444755049
31 
33.4237615317
31 
33.2450179104
31 
33.2521787368
31 
33.4460300474
31 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row33.3444755049
2nd row33.4237615317
3rd row33.2450179104
4th row33.2521787368
5th row33.4460300474

Common Values

ValueCountFrequency (%)
33.3444755049 31
20.0%
33.4237615317 31
20.0%
33.2450179104 31
20.0%
33.2521787368 31
20.0%
33.4460300474 31
20.0%

Length

2023-12-10T18:59:46.757607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:47.003958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
33.3444755049 31
20.0%
33.4237615317 31
20.0%
33.2450179104 31
20.0%
33.2521787368 31
20.0%
33.4460300474 31
20.0%

TRRSRT_LO
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
126.5364394223
31 
126.5581440803
31 
126.4156521304
31 
126.6231006558
31 
126.3043961883
31 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row126.5364394223
2nd row126.5581440803
3rd row126.4156521304
4th row126.6231006558
5th row126.3043961883

Common Values

ValueCountFrequency (%)
126.5364394223 31
20.0%
126.5581440803 31
20.0%
126.4156521304 31
20.0%
126.6231006558 31
20.0%
126.3043961883 31
20.0%

Length

2023-12-10T18:59:47.236638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:59:47.509637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
126.5364394223 31
20.0%
126.5581440803 31
20.0%
126.4156521304 31
20.0%
126.6231006558 31
20.0%
126.3043961883 31
20.0%

Interactions

2023-12-10T18:59:39.229140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:34.650476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:35.886066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:36.943836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:38.054717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:39.370501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:34.834225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:36.052464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:37.086188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:38.278533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:39.547058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:35.038243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:36.241607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:37.343152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:38.447919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:39.731703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:35.270371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:36.547357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:37.558036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:38.721230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:40.504558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:35.551712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:36.764300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:37.735849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:59:38.943743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:59:47.754210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SEQ_NOSRCHWRD_NMMOBILE_SCCNT_VALUEPC_SCCNT_VALUESCCNT_SM_VALUESCCNT_DEAREA_ADDRTRRSRT_LATRRSRT_LO
SEQ_NO1.0001.0000.4980.6060.4560.0001.0001.0001.000
SRCHWRD_NM1.0001.0000.4950.6030.4500.0001.0001.0001.000
MOBILE_SCCNT_VALUE0.4980.4951.0000.7000.7100.3210.4950.4950.495
PC_SCCNT_VALUE0.6060.6030.7001.0000.9930.5790.6030.6030.603
SCCNT_SM_VALUE0.4560.4500.7100.9931.0000.5700.4500.4500.450
SCCNT_DE0.0000.0000.3210.5790.5701.0000.0000.0000.000
AREA_ADDR1.0001.0000.4950.6030.4500.0001.0001.0001.000
TRRSRT_LA1.0001.0000.4950.6030.4500.0001.0001.0001.000
TRRSRT_LO1.0001.0000.4950.6030.4500.0001.0001.0001.000
2023-12-10T18:59:47.986460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
TRRSRT_LOTRRSRT_LAAREA_ADDRSRCHWRD_NM
TRRSRT_LO1.0001.0001.0001.000
TRRSRT_LA1.0001.0001.0001.000
AREA_ADDR1.0001.0001.0001.000
SRCHWRD_NM1.0001.0001.0001.000
2023-12-10T18:59:48.185744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SEQ_NOMOBILE_SCCNT_VALUEPC_SCCNT_VALUESCCNT_SM_VALUESCCNT_DESRCHWRD_NMAREA_ADDRTRRSRT_LATRRSRT_LO
SEQ_NO1.000-0.034-0.247-0.2470.2001.0001.0001.0001.000
MOBILE_SCCNT_VALUE-0.0341.0000.2580.3440.3510.3620.3620.3620.362
PC_SCCNT_VALUE-0.2470.2581.0000.9930.5570.2630.2630.2630.263
SCCNT_SM_VALUE-0.2470.3440.9931.0000.5850.1810.1810.1810.181
SCCNT_DE0.2000.3510.5570.5851.0000.0000.0000.0000.000
SRCHWRD_NM1.0000.3620.2630.1810.0001.0001.0001.0001.000
AREA_ADDR1.0000.3620.2630.1810.0001.0001.0001.0001.000
TRRSRT_LA1.0000.3620.2630.1810.0001.0001.0001.0001.000
TRRSRT_LO1.0000.3620.2630.1810.0001.0001.0001.0001.000

Missing values

2023-12-10T18:59:40.788738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:59:41.209506image/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

SEQ_NOSRCHWRD_NMUPPER_CTGRY_NMLWPRT_CTGRY_NMMOBILE_SCCNT_VALUEPC_SCCNT_VALUESCCNT_SM_VALUESCCNT_DEAREA_NMAREA_ADDRTRRSRT_LATRRSRT_LO
027674한라산백록담여행관광지1027428420210101제주제주특별자치도 서귀포시 토평동33.344476126.536439
145991관음사여행관광지1422724120210101제주제주특별자치도 제주시 산록북로 660(아라일동)33.423762126.558144
217954퍼시픽리솜여행관광지823023820210101제주제주특별자치도 서귀포시 중문관광로 154-1733.245018126.415652
32044쇠소깍여행관광지2827630420210101제주제주특별자치도 서귀포시 쇠소깍로 128(하효동)33.252179126.623101
423099곽지해수욕장여행관광지1724926620210101제주제주특별자치도 제주시 애월읍 금성5길33.44603126.304396
517955퍼시픽리솜여행관광지017817820210102제주제주특별자치도 서귀포시 중문관광로 154-1733.245018126.415652
627675한라산백록담여행관광지1523925420210102제주제주특별자치도 서귀포시 토평동33.344476126.536439
745992관음사여행관광지1320822120210102제주제주특별자치도 제주시 산록북로 660(아라일동)33.423762126.558144
82045쇠소깍여행관광지3728332020210102제주제주특별자치도 서귀포시 쇠소깍로 128(하효동)33.252179126.623101
923100곽지해수욕장여행관광지1227028220210102제주제주특별자치도 제주시 애월읍 금성5길33.44603126.304396
SEQ_NOSRCHWRD_NMUPPER_CTGRY_NMLWPRT_CTGRY_NMMOBILE_SCCNT_VALUEPC_SCCNT_VALUESCCNT_SM_VALUESCCNT_DEAREA_NMAREA_ADDRTRRSRT_LATRRSRT_LO
14546020관음사여행관광지1719220920210130제주제주특별자치도 제주시 산록북로 660(아라일동)33.423762126.558144
14617983퍼시픽리솜여행관광지2362264520210130제주제주특별자치도 서귀포시 중문관광로 154-1733.245018126.415652
14723128곽지해수욕장여행관광지3544548020210130제주제주특별자치도 제주시 애월읍 금성5길33.44603126.304396
1482073쇠소깍여행관광지10751962620210130제주제주특별자치도 서귀포시 쇠소깍로 128(하효동)33.252179126.623101
14927703한라산백록담여행관광지2430733120210130제주제주특별자치도 서귀포시 토평동33.344476126.536439
15046021관음사여행관광지2723225920210131제주제주특별자치도 제주시 산록북로 660(아라일동)33.423762126.558144
15117984퍼시픽리솜여행관광지2079181120210131제주제주특별자치도 서귀포시 중문관광로 154-1733.245018126.415652
15227704한라산백록담여행관광지2129331420210131제주제주특별자치도 서귀포시 토평동33.344476126.536439
15323129곽지해수욕장여행관광지3545248720210131제주제주특별자치도 제주시 애월읍 금성5길33.44603126.304396
1542074쇠소깍여행관광지10164774820210131제주제주특별자치도 서귀포시 쇠소깍로 128(하효동)33.252179126.623101