Overview

Dataset statistics

Number of variables17
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows13
Duplicate rows (%)13.0%
Total size in memory14.2 KiB
Average record size in memory145.3 B

Variable types

Categorical10
Numeric7

Alerts

ctprvn_nm has constant value ""Constant
FILE_NAME has constant value ""Constant
base_ymd has constant value ""Constant
Dataset has 13 (13.0%) duplicate rowsDuplicates
adstrd_nm is highly overall correlated with x_cd and 9 other fieldsHigh correlation
rdnm_addr is highly overall correlated with x_cd and 9 other fieldsHigh correlation
fclt_nm is highly overall correlated with x_cd and 9 other fieldsHigh correlation
id is highly overall correlated with x_cd and 9 other fieldsHigh correlation
legalemd_nm is highly overall correlated with x_cd and 9 other fieldsHigh correlation
sgnr_nm is highly overall correlated with x_cd and 9 other fieldsHigh correlation
x_cd is highly overall correlated with legaldong_cd and 7 other fieldsHigh correlation
y_cd is highly overall correlated with legaldong_cd and 7 other fieldsHigh correlation
legaldong_cd is highly overall correlated with x_cd and 8 other fieldsHigh correlation
adstrd_cd is highly overall correlated with x_cd and 8 other fieldsHigh correlation
rdnmaddr_cd is highly overall correlated with id and 5 other fieldsHigh correlation
rnk is highly overall correlated with search_monthHigh correlation
search_month is highly overall correlated with rnkHigh correlation
sgnr_nm is highly imbalanced (80.6%)Imbalance

Reproduction

Analysis started2023-12-10 10:14:37.927434
Analysis finished2023-12-10 10:14:49.482008
Duration11.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC488PO19N000181
24 
KC488PO19N000183
15 
KC488PO19N000186
15 
KC488PO19N000187
15 
KC488PO19N000182
12 
Other values (3)
19 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC488PO19N000181
2nd rowKC488PO19N000181
3rd rowKC488PO19N000181
4th rowKC488PO19N000181
5th rowKC488PO19N000181

Common Values

ValueCountFrequency (%)
KC488PO19N000181 24
24.0%
KC488PO19N000183 15
15.0%
KC488PO19N000186 15
15.0%
KC488PO19N000187 15
15.0%
KC488PO19N000182 12
12.0%
KC488PO19N000185 12
12.0%
KC488PO19N000184 4
 
4.0%
KC488PO19N000188 3
 
3.0%

Length

2023-12-10T19:14:49.602946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:49.808474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc488po19n000181 24
24.0%
kc488po19n000183 15
15.0%
kc488po19n000186 15
15.0%
kc488po19n000187 15
15.0%
kc488po19n000182 12
12.0%
kc488po19n000185 12
12.0%
kc488po19n000184 4
 
4.0%
kc488po19n000188 3
 
3.0%

fclt_nm
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
팔봉산감자축제
24 
삼길포우럭축제
15 
서산해미읍성축제
15 
서산국화축제
15 
서산6쪽마늘축제
12 
Other values (3)
19 

Length

Max length9
Median length8
Mean length7.29
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
팔봉산감자축제 24
24.0%
삼길포우럭축제 15
15.0%
서산해미읍성축제 15
15.0%
서산국화축제 15
15.0%
서산6쪽마늘축제 12
12.0%
서산어리굴젓축제 12
12.0%
서산뻘낙지먹물축제 4
 
4.0%
논산딸기축제 3
 
3.0%

Length

2023-12-10T19:14:50.053453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:50.272010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
팔봉산감자축제 24
24.0%
삼길포우럭축제 15
15.0%
서산해미읍성축제 15
15.0%
서산국화축제 15
15.0%
서산6쪽마늘축제 12
12.0%
서산어리굴젓축제 12
12.0%
서산뻘낙지먹물축제 4
 
4.0%
논산딸기축제 3
 
3.0%

x_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.753384
Minimum36.209229
Maximum37.001016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:50.510888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.209229
5-th percentile36.603755
Q136.669326
median36.713557
Q336.817618
95-th percentile37.001016
Maximum37.001016
Range0.79178671
Interquartile range (IQR)0.14829187

Descriptive statistics

Standard deviation0.15534818
Coefficient of variation (CV)0.0042267722
Kurtosis2.945926
Mean36.753384
Median Absolute Deviation (MAD)0.1040612
Skewness-0.80240373
Sum3675.3384
Variance0.024133057
MonotonicityNot monotonic
2023-12-10T19:14:50.718416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
36.7135571698 27
27.0%
36.81761837 24
24.0%
37.0010156 15
15.0%
36.6693265 15
15.0%
36.6037549404 12
12.0%
36.8804015609 4
 
4.0%
36.2092288864 3
 
3.0%
ValueCountFrequency (%)
36.2092288864 3
 
3.0%
36.6037549404 12
12.0%
36.6693265 15
15.0%
36.7135571698 27
27.0%
36.81761837 24
24.0%
36.8804015609 4
 
4.0%
37.0010156 15
15.0%
ValueCountFrequency (%)
37.0010156 15
15.0%
36.8804015609 4
 
4.0%
36.81761837 24
24.0%
36.7135571698 27
27.0%
36.6693265 15
15.0%
36.6037549404 12
12.0%
36.2092288864 3
 
3.0%

y_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.48184
Minimum126.36624
Maximum127.08199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:50.916499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.36624
5-th percentile126.36624
Q1126.38455
median126.45158
Q3126.55038
95-th percentile126.55038
Maximum127.08199
Range0.7157423
Interquartile range (IQR)0.16583696

Descriptive statistics

Standard deviation0.13043586
Coefficient of variation (CV)0.0010312616
Kurtosis11.547126
Mean126.48184
Median Absolute Deviation (MAD)0.08533197
Skewness2.8524663
Sum12648.184
Variance0.017013514
MonotonicityNot monotonic
2023-12-10T19:14:51.104962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
126.5503841589 27
27.0%
126.3662446 24
24.0%
126.45157657 15
15.0%
126.536271 15
15.0%
126.4110015619 12
12.0%
126.3845472 4
 
4.0%
127.0819869 3
 
3.0%
ValueCountFrequency (%)
126.3662446 24
24.0%
126.3845472 4
 
4.0%
126.4110015619 12
12.0%
126.45157657 15
15.0%
126.536271 15
15.0%
126.5503841589 27
27.0%
127.0819869 3
 
3.0%
ValueCountFrequency (%)
127.0819869 3
 
3.0%
126.5503841589 27
27.0%
126.536271 15
15.0%
126.45157657 15
15.0%
126.4110015619 12
12.0%
126.3845472 4
 
4.0%
126.3662446 24
24.0%

ctprvn_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충청남도
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 100
100.0%

Length

2023-12-10T19:14:51.327362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:51.486725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 100
100.0%

sgnr_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서산시
97 
논산시
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서산시 97
97.0%
논산시 3
 
3.0%

Length

2023-12-10T19:14:51.662233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:51.822385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서산시 97
97.0%
논산시 3
 
3.0%

legaldong_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4210937 × 109
Minimum4.421025 × 109
Maximum4.4230103 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:51.955765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.421025 × 109
5-th percentile4.421025 × 109
Q14.421032 × 109
median4.421033 × 109
Q34.421039 × 109
95-th percentile4.42104 × 109
Maximum4.4230103 × 109
Range1985272
Interquartile range (IQR)6987

Descriptive statistics

Standard deviation338788.55
Coefficient of variation (CV)7.6630031 × 10-5
Kurtosis29.883414
Mean4.4210937 × 109
Median Absolute Deviation (MAD)5999
Skewness5.5926983
Sum4.4210937 × 1011
Variance1.1477768 × 1011
MonotonicityNot monotonic
2023-12-10T19:14:52.228776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4421039021 27
27.0%
4421033022 24
24.0%
4421025028 15
15.0%
4421040021 15
15.0%
4421032034 12
12.0%
4421034025 4
 
4.0%
4423010300 3
 
3.0%
ValueCountFrequency (%)
4421025028 15
15.0%
4421032034 12
12.0%
4421033022 24
24.0%
4421034025 4
 
4.0%
4421039021 27
27.0%
4421040021 15
15.0%
4423010300 3
 
3.0%
ValueCountFrequency (%)
4423010300 3
 
3.0%
4421040021 15
15.0%
4421039021 27
27.0%
4421034025 4
 
4.0%
4421033022 24
24.0%
4421032034 12
12.0%
4421025028 15
15.0%

legalemd_nm
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
해미면
27 
팔봉면
24 
대산읍
15 
고북면
15 
부석면
12 
Other values (2)
7 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해미면 27
27.0%
팔봉면 24
24.0%
대산읍 15
15.0%
고북면 15
15.0%
부석면 12
12.0%
지곡면 4
 
4.0%
대교동 3
 
3.0%

Length

2023-12-10T19:14:52.758415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:52.950914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해미면 27
27.0%
팔봉면 24
24.0%
대산읍 15
15.0%
고북면 15
15.0%
부석면 12
12.0%
지곡면 4
 
4.0%
대교동 3
 
3.0%

adstrd_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.421095 × 109
Minimum4.421025 × 109
Maximum4.423052 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:53.148872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.421025 × 109
5-th percentile4.421025 × 109
Q14.421032 × 109
median4.421033 × 109
Q34.421039 × 109
95-th percentile4.42104 × 109
Maximum4.423052 × 109
Range2027000
Interquartile range (IQR)7000

Descriptive statistics

Standard deviation345941.28
Coefficient of variation (CV)7.8247875 × 10-5
Kurtosis29.883986
Mean4.421095 × 109
Median Absolute Deviation (MAD)6000
Skewness5.592776
Sum4.421095 × 1011
Variance1.1967537 × 1011
MonotonicityNot monotonic
2023-12-10T19:14:53.350074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4421039000 27
27.0%
4421033000 24
24.0%
4421025000 15
15.0%
4421040000 15
15.0%
4421032000 12
12.0%
4421034000 4
 
4.0%
4423052000 3
 
3.0%
ValueCountFrequency (%)
4421025000 15
15.0%
4421032000 12
12.0%
4421033000 24
24.0%
4421034000 4
 
4.0%
4421039000 27
27.0%
4421040000 15
15.0%
4423052000 3
 
3.0%
ValueCountFrequency (%)
4423052000 3
 
3.0%
4421040000 15
15.0%
4421039000 27
27.0%
4421034000 4
 
4.0%
4421033000 24
24.0%
4421032000 12
12.0%
4421025000 15
15.0%

adstrd_nm
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
해미면
27 
팔봉면
24 
대산읍
15 
고북면
15 
부석면
12 
Other values (2)
7 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해미면 27
27.0%
팔봉면 24
24.0%
대산읍 15
15.0%
고북면 15
15.0%
부석면 12
12.0%
지곡면 4
 
4.0%
부창동 3
 
3.0%

Length

2023-12-10T19:14:53.592034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:53.842617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해미면 27
27.0%
팔봉면 24
24.0%
대산읍 15
15.0%
고북면 15
15.0%
부석면 12
12.0%
지곡면 4
 
4.0%
부창동 3
 
3.0%

rdnmaddr_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4210986 × 1011
Minimum4.4210325 × 1011
Maximum4.4230326 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:54.151827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.4210325 × 1011
5-th percentile4.4210325 × 1011
Q14.4210325 × 1011
median4.4210325 × 1011
Q34.4210456 × 1011
95-th percentile4.4210456 × 1011
Maximum4.4230326 × 1011
Range2.0000099 × 108
Interquartile range (IQR)1308283

Descriptive statistics

Standard deviation34189234
Coefficient of variation (CV)7.7331987 × 10-5
Kurtosis29.874249
Mean4.4210986 × 1011
Median Absolute Deviation (MAD)145
Skewness5.5914574
Sum4.4210986 × 1013
Variance1.1689037 × 1015
MonotonicityNot monotonic
2023-12-10T19:14:54.428551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
442103254016 27
27.0%
442103254161 24
24.0%
442104562342 15
15.0%
442104562299 15
15.0%
442104562017 12
12.0%
442104562475 4
 
4.0%
442303255004 3
 
3.0%
ValueCountFrequency (%)
442103254016 27
27.0%
442103254161 24
24.0%
442104562017 12
12.0%
442104562299 15
15.0%
442104562342 15
15.0%
442104562475 4
 
4.0%
442303255004 3
 
3.0%
ValueCountFrequency (%)
442303255004 3
 
3.0%
442104562475 4
 
4.0%
442104562342 15
15.0%
442104562299 15
15.0%
442104562017 12
12.0%
442103254161 24
24.0%
442103254016 27
27.0%

rdnm_addr
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충청남도 서산시 해미면 남문2로 143
27 
충청남도 서산시 팔봉면 팔봉산로 100
24 
충청남도 서산시 대산읍 삼길포3길 8
15 
충청남도 서산시 고북면 복남골길 31-1
15 
충청남도 서산시 부석면 간월도1길 119-29
12 
Other values (2)
7 

Length

Max length25
Median length21
Mean length21.33
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 서산시 팔봉면 팔봉산로 100
2nd row충청남도 서산시 팔봉면 팔봉산로 100
3rd row충청남도 서산시 팔봉면 팔봉산로 100
4th row충청남도 서산시 팔봉면 팔봉산로 100
5th row충청남도 서산시 팔봉면 팔봉산로 100

Common Values

ValueCountFrequency (%)
충청남도 서산시 해미면 남문2로 143 27
27.0%
충청남도 서산시 팔봉면 팔봉산로 100 24
24.0%
충청남도 서산시 대산읍 삼길포3길 8 15
15.0%
충청남도 서산시 고북면 복남골길 31-1 15
15.0%
충청남도 서산시 부석면 간월도1길 119-29 12
12.0%
충청남도 서산시 지곡면 어름들2길 66 4
 
4.0%
충청남도 논산시 강변로 370 3
 
3.0%

Length

2023-12-10T19:14:54.765553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:54.949503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 100
20.1%
서산시 97
19.5%
해미면 27
 
5.4%
남문2로 27
 
5.4%
143 27
 
5.4%
팔봉면 24
 
4.8%
팔봉산로 24
 
4.8%
100 24
 
4.8%
31-1 15
 
3.0%
복남골길 15
 
3.0%
Other values (13) 117
23.5%

search_month
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019-08
8 
2018-10
8 
2019-06
7 
2019-05
7 
2019-04
7 
Other values (10)
63 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-08
2nd row2019-08
3rd row2019-07
4th row2019-07
5th row2019-06

Common Values

ValueCountFrequency (%)
2019-08 8
 
8.0%
2018-10 8
 
8.0%
2019-06 7
 
7.0%
2019-05 7
 
7.0%
2019-04 7
 
7.0%
2018-12 7
 
7.0%
2018-11 7
 
7.0%
2019-11 7
 
7.0%
2019-10 7
 
7.0%
2019-07 6
 
6.0%
Other values (5) 29
29.0%

Length

2023-12-10T19:14:55.172753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-08 8
 
8.0%
2018-10 8
 
8.0%
2019-06 7
 
7.0%
2019-05 7
 
7.0%
2019-04 7
 
7.0%
2018-12 7
 
7.0%
2018-11 7
 
7.0%
2019-11 7
 
7.0%
2019-10 7
 
7.0%
2019-07 6
 
6.0%
Other values (5) 29
29.0%

search_cnt
Real number (ℝ)

Distinct62
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2138.58
Minimum12
Maximum51410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:55.413493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile16.95
Q137.5
median160
Q3747.5
95-th percentile13480
Maximum51410
Range51398
Interquartile range (IQR)710

Descriptive statistics

Standard deviation6531.1277
Coefficient of variation (CV)3.0539553
Kurtosis33.984739
Mean2138.58
Median Absolute Deviation (MAD)141
Skewness5.2691904
Sum213858
Variance42655629
MonotonicityNot monotonic
2023-12-10T19:14:56.133776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 7
 
7.0%
20 7
 
7.0%
130 5
 
5.0%
60 4
 
4.0%
120 4
 
4.0%
310 3
 
3.0%
110 3
 
3.0%
2530 2
 
2.0%
300 2
 
2.0%
17 2
 
2.0%
Other values (52) 61
61.0%
ValueCountFrequency (%)
12 1
 
1.0%
13 2
 
2.0%
15 1
 
1.0%
16 1
 
1.0%
17 2
 
2.0%
18 1
 
1.0%
19 2
 
2.0%
20 7
7.0%
29 1
 
1.0%
30 7
7.0%
ValueCountFrequency (%)
51410 1
1.0%
21460 1
1.0%
21070 1
1.0%
17970 1
1.0%
15380 1
1.0%
13380 1
1.0%
10830 1
1.0%
10140 2
2.0%
4410 1
1.0%
2530 2
2.0%

rnk
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.63
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:56.361278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median9
Q313
95-th percentile25
Maximum29
Range28
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.8955483
Coefficient of variation (CV)0.71604863
Kurtosis0.64633341
Mean9.63
Median Absolute Deviation (MAD)4
Skewness1.0041146
Sum963
Variance47.548586
MonotonicityNot monotonic
2023-12-10T19:14:56.714318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 8
 
8.0%
7 7
 
7.0%
11 7
 
7.0%
9 7
 
7.0%
3 7
 
7.0%
4 6
 
6.0%
2 6
 
6.0%
13 5
 
5.0%
15 5
 
5.0%
12 5
 
5.0%
Other values (12) 37
37.0%
ValueCountFrequency (%)
1 8
8.0%
2 6
6.0%
3 7
7.0%
4 6
6.0%
5 5
5.0%
6 5
5.0%
7 7
7.0%
8 5
5.0%
9 7
7.0%
10 5
5.0%
ValueCountFrequency (%)
29 2
 
2.0%
27 2
 
2.0%
25 2
 
2.0%
23 2
 
2.0%
21 2
 
2.0%
19 2
 
2.0%
17 2
 
2.0%
15 5
5.0%
14 3
3.0%
13 5
5.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_594_WNTY_FSTV_TRND_MAP_2019
100 

Length

Max length30
Median length30
Mean length30
Min length30

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_594_WNTY_FSTV_TRND_MAP_2019
2nd rowKC_594_WNTY_FSTV_TRND_MAP_2019
3rd rowKC_594_WNTY_FSTV_TRND_MAP_2019
4th rowKC_594_WNTY_FSTV_TRND_MAP_2019
5th rowKC_594_WNTY_FSTV_TRND_MAP_2019

Common Values

ValueCountFrequency (%)
KC_594_WNTY_FSTV_TRND_MAP_2019 100
100.0%

Length

2023-12-10T19:14:56.948390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:57.095557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_594_wnty_fstv_trnd_map_2019 100
100.0%

base_ymd
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200219
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200219
2nd row20200219
3rd row20200219
4th row20200219
5th row20200219

Common Values

ValueCountFrequency (%)
20200219 100
100.0%

Length

2023-12-10T19:14:57.257911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:57.404352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200219 100
100.0%

Interactions

2023-12-10T19:14:47.471198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:39.198922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:40.308116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:41.649539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:43.177227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:44.984183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:46.305645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:47.670093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:39.342385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:40.479825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:41.829803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:43.391830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:45.165241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:46.522663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:47.834213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:39.508253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:40.641388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:42.084630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:43.607965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:45.341079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:46.691536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:48.094176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:39.694839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:40.832146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:42.393034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:43.805225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:45.575506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:46.875120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:48.291061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:39.853516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:41.017045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:42.600414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:44.010015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:45.757897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:47.031543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:48.463981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:40.027636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:41.211449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:42.814952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:44.236793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:45.958686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:47.195876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:48.618193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:40.147664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:41.390187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:43.003823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:44.397727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:46.137176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:14:47.316035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:14:57.533584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
idfclt_nmx_cdy_cdsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrsearch_monthsearch_cntrnk
id1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.316
fclt_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.316
x_cd1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.379
y_cd1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.1350.274
sgnr_nm1.0001.0001.0001.0001.0000.9621.0000.9621.0000.9621.0000.3230.0000.222
legaldong_cd1.0001.0001.0001.0000.9621.0001.0000.9621.0000.9611.0000.3530.0000.240
legalemd_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.379
adstrd_cd1.0001.0001.0001.0000.9620.9621.0001.0001.0000.9611.0000.3530.0000.240
adstrd_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.379
rdnmaddr_cd1.0001.0001.0001.0000.9620.9611.0000.9611.0001.0001.0000.4090.0000.287
rdnm_addr1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.379
search_month0.0000.0000.0000.0000.3230.3530.0000.3530.0000.4090.0001.0000.3000.869
search_cnt0.0000.0000.0000.1350.0000.0000.0000.0000.0000.0000.0000.3001.0000.000
rnk0.3160.3160.3790.2740.2220.2400.3790.2400.3790.2870.3790.8690.0001.000
2023-12-10T19:14:57.787105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
adstrd_nmrdnm_addrfclt_nmidlegalemd_nmsgnr_nmsearch_month
adstrd_nm1.0001.0000.9950.9951.0000.9740.000
rdnm_addr1.0001.0000.9950.9951.0000.9740.000
fclt_nm0.9950.9951.0001.0000.9950.9690.000
id0.9950.9951.0001.0000.9950.9690.000
legalemd_nm1.0001.0000.9950.9951.0000.9740.000
sgnr_nm0.9740.9740.9690.9690.9741.0000.272
search_month0.0000.0000.0000.0000.0000.2721.000
2023-12-10T19:14:57.993395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
x_cdy_cdlegaldong_cdadstrd_cdrdnmaddr_cdsearch_cntrnkidfclt_nmsgnr_nmlegalemd_nmadstrd_nmrdnm_addrsearch_month
x_cd1.000-0.405-0.552-0.5520.138-0.0000.2670.9950.9950.9741.0001.0001.0000.000
y_cd-0.4051.0000.6030.603-0.2390.269-0.4370.9790.9790.9900.9840.9840.9840.000
legaldong_cd-0.5520.6031.0001.000-0.2590.198-0.1710.9690.9690.8260.9740.9740.9740.272
adstrd_cd-0.5520.6031.0001.000-0.2590.198-0.1710.9690.9690.8260.9740.9740.9740.272
rdnmaddr_cd0.138-0.239-0.259-0.2591.0000.106-0.2140.9690.9690.8260.9740.9740.9740.272
search_cnt-0.0000.2690.1980.1980.1061.000-0.0860.0000.0000.0000.0000.0000.0000.132
rnk0.267-0.437-0.171-0.171-0.214-0.0861.0000.1660.1660.1600.2090.2090.2090.530
id0.9950.9790.9690.9690.9690.0000.1661.0001.0000.9690.9950.9950.9950.000
fclt_nm0.9950.9790.9690.9690.9690.0000.1661.0001.0000.9690.9950.9950.9950.000
sgnr_nm0.9740.9900.8260.8260.8260.0000.1600.9690.9691.0000.9740.9740.9740.272
legalemd_nm1.0000.9840.9740.9740.9740.0000.2090.9950.9950.9741.0001.0001.0000.000
adstrd_nm1.0000.9840.9740.9740.9740.0000.2090.9950.9950.9741.0001.0001.0000.000
rdnm_addr1.0000.9840.9740.9740.9740.0000.2090.9950.9950.9741.0001.0001.0000.000
search_month0.0000.0000.2720.2720.2720.1320.5300.0000.0000.2720.0000.0000.0001.000

Missing values

2023-12-10T19:14:48.948386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:14:49.334357image/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

idfclt_nmx_cdy_cdctprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrsearch_monthsearch_cntrnkFILE_NAMEbase_ymd
0KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-08607KC_594_WNTY_FSTV_TRND_MAP_201920200219
1KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-08607KC_594_WNTY_FSTV_TRND_MAP_201920200219
2KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-073109KC_594_WNTY_FSTV_TRND_MAP_201920200219
3KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-073109KC_594_WNTY_FSTV_TRND_MAP_201920200219
4KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-061014011KC_594_WNTY_FSTV_TRND_MAP_201920200219
5KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-061014011KC_594_WNTY_FSTV_TRND_MAP_201920200219
6KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-05143013KC_594_WNTY_FSTV_TRND_MAP_201920200219
7KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-05143013KC_594_WNTY_FSTV_TRND_MAP_201920200219
8KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-0429015KC_594_WNTY_FSTV_TRND_MAP_201920200219
9KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-0429015KC_594_WNTY_FSTV_TRND_MAP_201920200219
idfclt_nmx_cdy_cdctprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrsearch_monthsearch_cntrnkFILE_NAMEbase_ymd
90KC488PO19N000187서산국화축제36.669326126.536271충청남도서산시4421040021고북면4421040000고북면442104562299충청남도 서산시 고북면 복남골길 31-12019-031709KC_594_WNTY_FSTV_TRND_MAP_201920200219
91KC488PO19N000187서산국화축제36.669326126.536271충청남도서산시4421040021고북면4421040000고북면442104562299충청남도 서산시 고북면 복남골길 31-12019-026010KC_594_WNTY_FSTV_TRND_MAP_201920200219
92KC488PO19N000187서산국화축제36.669326126.536271충청남도서산시4421040021고북면4421040000고북면442104562299충청남도 서산시 고북면 복남골길 31-12019-018011KC_594_WNTY_FSTV_TRND_MAP_201920200219
93KC488PO19N000187서산국화축제36.669326126.536271충청남도서산시4421040021고북면4421040000고북면442104562299충청남도 서산시 고북면 복남골길 31-12018-1230012KC_594_WNTY_FSTV_TRND_MAP_201920200219
94KC488PO19N000187서산국화축제36.669326126.536271충청남도서산시4421040021고북면4421040000고북면442104562299충청남도 서산시 고북면 복남골길 31-12018-111083013KC_594_WNTY_FSTV_TRND_MAP_201920200219
95KC488PO19N000187서산국화축제36.669326126.536271충청남도서산시4421040021고북면4421040000고북면442104562299충청남도 서산시 고북면 복남골길 31-12018-102146014KC_594_WNTY_FSTV_TRND_MAP_201920200219
96KC488PO19N000187서산국화축제36.669326126.536271충청남도서산시4421040021고북면4421040000고북면442104562299충청남도 서산시 고북면 복남골길 31-12018-09241015KC_594_WNTY_FSTV_TRND_MAP_201920200219
97KC488PO19N000188논산딸기축제36.209229127.081987충청남도논산시4423010300대교동4423052000부창동442303255004충청남도 논산시 강변로 3702019-1125301KC_594_WNTY_FSTV_TRND_MAP_201920200219
98KC488PO19N000188논산딸기축제36.209229127.081987충청남도논산시4423010300대교동4423052000부창동442303255004충청남도 논산시 강변로 3702019-1125301KC_594_WNTY_FSTV_TRND_MAP_201920200219
99KC488PO19N000188논산딸기축제36.209229127.081987충청남도논산시4423010300대교동4423052000부창동442303255004충청남도 논산시 강변로 3702019-1016003KC_594_WNTY_FSTV_TRND_MAP_201920200219

Duplicate rows

Most frequently occurring

idfclt_nmx_cdy_cdctprvn_nmsgnr_nmlegaldong_cdlegalemd_nmadstrd_cdadstrd_nmrdnmaddr_cdrdnm_addrsearch_monthsearch_cntrnkFILE_NAMEbase_ymd# duplicates
0KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002018-0912029KC_594_WNTY_FSTV_TRND_MAP_2019202002192
1KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002018-1013027KC_594_WNTY_FSTV_TRND_MAP_2019202002192
2KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002018-117025KC_594_WNTY_FSTV_TRND_MAP_2019202002192
3KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002018-122023KC_594_WNTY_FSTV_TRND_MAP_2019202002192
4KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-013021KC_594_WNTY_FSTV_TRND_MAP_2019202002192
5KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-023019KC_594_WNTY_FSTV_TRND_MAP_2019202002192
6KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-0313017KC_594_WNTY_FSTV_TRND_MAP_2019202002192
7KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-0429015KC_594_WNTY_FSTV_TRND_MAP_2019202002192
8KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-05143013KC_594_WNTY_FSTV_TRND_MAP_2019202002192
9KC488PO19N000181팔봉산감자축제36.817618126.366245충청남도서산시4421033022팔봉면4421033000팔봉면442103254161충청남도 서산시 팔봉면 팔봉산로 1002019-061014011KC_594_WNTY_FSTV_TRND_MAP_2019202002192