Overview

Dataset statistics

Number of variables6
Number of observations365
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.7 KiB
Average record size in memory52.4 B

Variable types

DateTime1
Categorical1
Numeric4

Dataset

Description국립정신건강센터의 일별 외래환자수 현황 데이터 목록입니다. 해당 데이터에는 구분별(보험환자, 급여환자, 기타 환자) 외래환자 수 현황이 포함되어 있습니다.
Author보건복지부 국립정신건강센터
URLhttps://www.data.go.kr/data/15049248/fileData.do

Alerts

보험 is highly overall correlated with 급여 and 2 other fieldsHigh correlation
급여 is highly overall correlated with 보험 and 2 other fieldsHigh correlation
기타 is highly overall correlated with 보험 and 2 other fieldsHigh correlation
합계 is highly overall correlated with 보험 and 2 other fieldsHigh correlation
일자 has unique valuesUnique
보험 has 97 (26.6%) zerosZeros
급여 has 107 (29.3%) zerosZeros
기타 has 140 (38.4%) zerosZeros
합계 has 96 (26.3%) zerosZeros

Reproduction

Analysis started2023-12-12 16:31:39.140058
Analysis finished2023-12-12 16:31:41.091475
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

UNIQUE 

Distinct365
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2020-01-01 00:00:00
Maximum2020-12-31 00:00:00
2023-12-13T01:31:41.164326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:41.281130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

요일
Categorical

Distinct7
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
수
53 
목
53 
토
52 
일
52 
월
52 
Other values (2)
103 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수
2nd row목
3rd row금
4th row토
5th row일

Common Values

ValueCountFrequency (%)
수 53
14.5%
목 53
14.5%
토 52
14.2%
일 52
14.2%
월 52
14.2%
화 52
14.2%
금 51
14.0%

Length

2023-12-13T01:31:41.406362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:31:41.504453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수 53
14.5%
목 53
14.5%
토 52
14.2%
일 52
14.2%
월 52
14.2%
화 52
14.2%
금 51
14.0%

보험
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct138
Distinct (%)37.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean125.57808
Minimum0
Maximum386
Zeros97
Zeros (%)26.6%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-13T01:31:41.628398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median153
Q3193
95-th percentile255
Maximum386
Range386
Interquartile range (IQR)193

Descriptive statistics

Standard deviation93.553138
Coefficient of variation (CV)0.74497983
Kurtosis-1.1776092
Mean125.57808
Median Absolute Deviation (MAD)57
Skewness-0.23699323
Sum45836
Variance8752.1896
MonotonicityNot monotonic
2023-12-13T01:31:41.814490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 97
26.6%
1 9
 
2.5%
2 6
 
1.6%
181 6
 
1.6%
170 5
 
1.4%
180 5
 
1.4%
153 4
 
1.1%
146 4
 
1.1%
155 4
 
1.1%
174 4
 
1.1%
Other values (128) 221
60.5%
ValueCountFrequency (%)
0 97
26.6%
1 9
 
2.5%
2 6
 
1.6%
3 2
 
0.5%
4 2
 
0.5%
85 1
 
0.3%
94 1
 
0.3%
100 1
 
0.3%
106 1
 
0.3%
109 1
 
0.3%
ValueCountFrequency (%)
386 1
0.3%
315 1
0.3%
313 1
0.3%
312 1
0.3%
292 1
0.3%
285 1
0.3%
280 1
0.3%
278 1
0.3%
277 2
0.5%
276 1
0.3%

급여
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct81
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.134247
Minimum0
Maximum184
Zeros107
Zeros (%)29.3%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-13T01:31:41.988730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median58
Q377
95-th percentile103.8
Maximum184
Range184
Interquartile range (IQR)77

Descriptive statistics

Standard deviation38.060046
Coefficient of variation (CV)0.7746134
Kurtosis-0.77350619
Mean49.134247
Median Absolute Deviation (MAD)26
Skewness0.0064305222
Sum17934
Variance1448.5671
MonotonicityNot monotonic
2023-12-13T01:31:42.140965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 107
29.3%
58 10
 
2.7%
62 7
 
1.9%
67 7
 
1.9%
65 7
 
1.9%
73 7
 
1.9%
82 7
 
1.9%
1 7
 
1.9%
64 6
 
1.6%
55 6
 
1.6%
Other values (71) 194
53.2%
ValueCountFrequency (%)
0 107
29.3%
1 7
 
1.9%
2 2
 
0.5%
22 1
 
0.3%
29 1
 
0.3%
32 1
 
0.3%
34 1
 
0.3%
35 1
 
0.3%
37 3
 
0.8%
40 3
 
0.8%
ValueCountFrequency (%)
184 1
 
0.3%
158 1
 
0.3%
143 1
 
0.3%
123 1
 
0.3%
121 1
 
0.3%
115 2
0.5%
112 3
0.8%
111 3
0.8%
110 1
 
0.3%
108 1
 
0.3%

기타
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1260274
Minimum0
Maximum60
Zeros140
Zeros (%)38.4%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-13T01:31:42.264155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum60
Range60
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.1437769
Coefficient of variation (CV)1.9490703
Kurtosis117.82558
Mean2.1260274
Median Absolute Deviation (MAD)1
Skewness9.3574257
Sum776
Variance17.170887
MonotonicityNot monotonic
2023-12-13T01:31:42.396305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 140
38.4%
2 59
16.2%
1 47
 
12.9%
3 44
 
12.1%
4 30
 
8.2%
5 23
 
6.3%
6 9
 
2.5%
7 8
 
2.2%
60 1
 
0.3%
37 1
 
0.3%
Other values (3) 3
 
0.8%
ValueCountFrequency (%)
0 140
38.4%
1 47
 
12.9%
2 59
16.2%
3 44
 
12.1%
4 30
 
8.2%
5 23
 
6.3%
6 9
 
2.5%
7 8
 
2.2%
9 1
 
0.3%
12 1
 
0.3%
ValueCountFrequency (%)
60 1
 
0.3%
37 1
 
0.3%
16 1
 
0.3%
12 1
 
0.3%
9 1
 
0.3%
7 8
 
2.2%
6 9
 
2.5%
5 23
6.3%
4 30
8.2%
3 44
12.1%

합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct156
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.83836
Minimum0
Maximum573
Zeros96
Zeros (%)26.3%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-13T01:31:42.600250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median217
Q3273
95-th percentile352.8
Maximum573
Range573
Interquartile range (IQR)273

Descriptive statistics

Standard deviation131.82722
Coefficient of variation (CV)0.74546735
Kurtosis-1.1387779
Mean176.83836
Median Absolute Deviation (MAD)81
Skewness-0.23015573
Sum64546
Variance17378.416
MonotonicityNot monotonic
2023-12-13T01:31:42.757764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 96
26.3%
3 7
 
1.9%
1 6
 
1.6%
242 5
 
1.4%
212 5
 
1.4%
243 5
 
1.4%
260 5
 
1.4%
2 5
 
1.4%
228 4
 
1.1%
164 4
 
1.1%
Other values (146) 223
61.1%
ValueCountFrequency (%)
0 96
26.3%
1 6
 
1.6%
2 5
 
1.4%
3 7
 
1.9%
4 1
 
0.3%
5 1
 
0.3%
108 1
 
0.3%
125 1
 
0.3%
142 1
 
0.3%
149 1
 
0.3%
ValueCountFrequency (%)
573 1
0.3%
476 1
0.3%
426 1
0.3%
401 1
0.3%
398 1
0.3%
397 1
0.3%
392 2
0.5%
391 2
0.5%
386 1
0.3%
380 1
0.3%

Interactions

2023-12-13T01:31:40.569790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.307147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.673915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:40.007560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:40.685027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.409498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.764484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:40.093426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:40.792101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.499073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.845687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:40.176974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:40.865352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.589699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:39.924624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:31:40.492239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:31:42.879404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요일보험급여기타합계
요일1.0000.6790.7210.2430.716
보험0.6791.0000.8700.0000.930
급여0.7210.8701.0000.0000.970
기타0.2430.0000.0001.0000.000
합계0.7160.9300.9700.0001.000
2023-12-13T01:31:42.993842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보험급여기타합계요일
보험1.0000.9190.6140.9920.444
급여0.9191.0000.6170.9550.472
기타0.6140.6171.0000.6300.123
합계0.9920.9550.6301.0000.467
요일0.4440.4720.1230.4671.000

Missing values

2023-12-13T01:31:40.961334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:31:41.054847image/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

일자요일보험급여기타합계
02020-01-01수0000
12020-01-02목225603288
22020-01-03금259595323
32020-01-04토2103
42020-01-05일3003
52020-01-06월229724305
62020-01-07화2471033353
72020-01-08수3861843573
82020-01-09목2571127376
92020-01-10금277894370
일자요일보험급여기타합계
3552020-12-22화219741294
3562020-12-23수205875297
3572020-12-24목181736260
3582020-12-25금0000
3592020-12-26토0000
3602020-12-27일0000
3612020-12-28월173822257
3622020-12-29화191670258
3632020-12-30수200631264
3642020-12-31목177671245