Overview

Dataset statistics

Number of variables4
Number of observations755
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.2 KiB
Average record size in memory34.2 B

Variable types

DateTime1
Categorical2
Numeric1

Dataset

Description한국철도공사 기관사 네비게이션에서 호출한 인터페이스의 호출 횟수 정보로 시스템 정보입니다.(1,2 : 낙석CCTV / 20 : 열차접근 / 30 : 반경내작업)
URLhttps://www.data.go.kr/data/15121114/fileData.do

Alerts

인터페이스 ID is highly overall correlated with 통계 횟수 and 1 other fieldsHigh correlation
통계 코드 is highly overall correlated with 통계 횟수 and 1 other fieldsHigh correlation
통계 횟수 is highly overall correlated with 통계 코드 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 23:00:22.316309
Analysis finished2023-12-12 23:00:22.798470
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계 일자
Date

Distinct237
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum2023-01-01 00:00:00
Maximum2023-08-25 00:00:00
2023-12-13T08:00:22.921844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:23.110350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

통계 코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
1
237 
30
237 
20
237 
2
44 

Length

Max length2
Median length2
Mean length1.6278146
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row30
3rd row20
4th row1
5th row20

Common Values

ValueCountFrequency (%)
1 237
31.4%
30 237
31.4%
20 237
31.4%
2 44
 
5.8%

Length

2023-12-13T08:00:23.267507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:00:23.396597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 237
31.4%
30 237
31.4%
20 237
31.4%
2 44
 
5.8%

통계 횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct749
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean271171.05
Minimum1
Maximum1230730
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-13T08:00:23.526994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1147
Q120529
median114481
Q3397491
95-th percentile1001997.9
Maximum1230730
Range1230729
Interquartile range (IQR)376962

Descriptive statistics

Standard deviation351462.42
Coefficient of variation (CV)1.2960912
Kurtosis-0.020290504
Mean271171.05
Median Absolute Deviation (MAD)96240
Skewness1.2372676
Sum2.0473415 × 108
Variance1.2352583 × 1011
MonotonicityNot monotonic
2023-12-13T08:00:23.669198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15050 2
 
0.3%
21733 2
 
0.3%
484 2
 
0.3%
18105 2
 
0.3%
4 2
 
0.3%
1 2
 
0.3%
14130 1
 
0.1%
245253 1
 
0.1%
148645 1
 
0.1%
1070311 1
 
0.1%
Other values (739) 739
97.9%
ValueCountFrequency (%)
1 2
0.3%
4 2
0.3%
10 1
0.1%
15 1
0.1%
17 1
0.1%
21 1
0.1%
24 1
0.1%
29 1
0.1%
46 1
0.1%
132 1
0.1%
ValueCountFrequency (%)
1230730 1
0.1%
1185345 1
0.1%
1183927 1
0.1%
1180803 1
0.1%
1170986 1
0.1%
1136745 1
0.1%
1132456 1
0.1%
1116133 1
0.1%
1114000 1
0.1%
1095776 1
0.1%

인터페이스 ID
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
SP_IF_CADS_CCTV_DIFC
281 
SP_IF_CADS_TRN_RTM_LOC
237 
SP_IF_CADS_WRK_PS_RTM_LOC
237 

Length

Max length25
Median length22
Mean length22.197351
Min length20

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSP_IF_CADS_CCTV_DIFC
2nd rowSP_IF_CADS_TRN_RTM_LOC
3rd rowSP_IF_CADS_WRK_PS_RTM_LOC
4th rowSP_IF_CADS_CCTV_DIFC
5th rowSP_IF_CADS_WRK_PS_RTM_LOC

Common Values

ValueCountFrequency (%)
SP_IF_CADS_CCTV_DIFC 281
37.2%
SP_IF_CADS_TRN_RTM_LOC 237
31.4%
SP_IF_CADS_WRK_PS_RTM_LOC 237
31.4%

Length

2023-12-13T08:00:23.847835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:00:23.959450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sp_if_cads_cctv_difc 281
37.2%
sp_if_cads_trn_rtm_loc 237
31.4%
sp_if_cads_wrk_ps_rtm_loc 237
31.4%

Interactions

2023-12-13T08:00:22.490452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:00:24.054848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계 코드통계 횟수인터페이스 ID
통계 코드1.0000.8241.000
통계 횟수0.8241.0000.875
인터페이스 ID1.0000.8751.000
2023-12-13T08:00:24.145232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인터페이스 ID통계 코드
인터페이스 ID1.0000.999
통계 코드0.9991.000
2023-12-13T08:00:24.248772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계 횟수통계 코드인터페이스 ID
통계 횟수1.0000.6550.806
통계 코드0.6551.0000.999
인터페이스 ID0.8060.9991.000

Missing values

2023-12-13T08:00:22.639952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:00:22.743784image/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

통계 일자통계 코드통계 횟수인터페이스 ID
02023-01-01114130SP_IF_CADS_CCTV_DIFC
12023-01-0130243805SP_IF_CADS_TRN_RTM_LOC
22023-01-012043486SP_IF_CADS_WRK_PS_RTM_LOC
32023-01-02117552SP_IF_CADS_CCTV_DIFC
42023-01-0220142703SP_IF_CADS_WRK_PS_RTM_LOC
52023-01-0230685116SP_IF_CADS_TRN_RTM_LOC
62023-01-0330849920SP_IF_CADS_TRN_RTM_LOC
72023-01-03120509SP_IF_CADS_CCTV_DIFC
82023-01-0320158811SP_IF_CADS_WRK_PS_RTM_LOC
92023-01-0430965705SP_IF_CADS_TRN_RTM_LOC
통계 일자통계 코드통계 횟수인터페이스 ID
7452023-08-2320114481SP_IF_CADS_WRK_PS_RTM_LOC
7462023-08-2330865109SP_IF_CADS_TRN_RTM_LOC
7472023-08-23120113SP_IF_CADS_CCTV_DIFC
7482023-08-2430998154SP_IF_CADS_TRN_RTM_LOC
7492023-08-24117701SP_IF_CADS_CCTV_DIFC
7502023-08-2420113201SP_IF_CADS_WRK_PS_RTM_LOC
7512023-08-252085869SP_IF_CADS_WRK_PS_RTM_LOC
7522023-08-25110278SP_IF_CADS_CCTV_DIFC
7532023-08-2530653300SP_IF_CADS_TRN_RTM_LOC
7542023-08-2524SP_IF_CADS_CCTV_DIFC