Overview

Dataset statistics

Number of variables10
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory87.8 B

Variable types

Numeric4
Text4
Categorical1
Boolean1

Dataset

Description대구광역시 서구 특수의료장비 관련 정보데이터 입니다. 의료기관 명, 의료기관 소재지, 자체병상 수, 공동활용 병상 수, 의료장비종류 등을 포함하고 있습니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/15088431/fileData.do

Alerts

순번 is highly overall correlated with 공동활용병상수 and 1 other fieldsHigh correlation
자체병상수 is highly overall correlated with 총병상수 and 1 other fieldsHigh correlation
공동활용병상수 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
총병상수 is highly overall correlated with 자체병상수 and 2 other fieldsHigh correlation
의료장비종류 is highly overall correlated with 공동이용여부High correlation
공동이용여부 is highly overall correlated with 순번 and 4 other fieldsHigh correlation
순번 has unique valuesUnique
자체병상수 has 12 (35.3%) zerosZeros
공동활용병상수 has 19 (55.9%) zerosZeros
총병상수 has 10 (29.4%) zerosZeros

Reproduction

Analysis started2024-03-14 23:16:13.732110
Analysis finished2024-03-14 23:16:18.931097
Duration5.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.5
Minimum1
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T08:16:19.042885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q19.25
median17.5
Q325.75
95-th percentile32.35
Maximum34
Range33
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation9.9582462
Coefficient of variation (CV)0.56904264
Kurtosis-1.2
Mean17.5
Median Absolute Deviation (MAD)8.5
Skewness0
Sum595
Variance99.166667
MonotonicityStrictly increasing
2024-03-15T08:16:19.280129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 1
 
2.9%
27 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
28 1
 
2.9%
19 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%
25 1
2.9%

의료기관명
Text

Distinct19
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-03-15T08:16:19.955297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10.5
Mean length7.9411765
Min length4

Characters and Unicode

Total characters270
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)32.4%

Sample

1st row대명의료재단서대구병원
2nd row디케어센터의원
3rd row디케어센터의원
4th row네이처영상의학과의원
5th row네이처영상의학과의원
ValueCountFrequency (%)
대명의료재단서대구병원 4
11.8%
대구의료원 3
 
8.8%
디케어센터의원 3
 
8.8%
참튼튼병원 3
 
8.8%
네이처영상의학과의원 3
 
8.8%
새동산병원 3
 
8.8%
인구보건복지협회가족보건의원 2
 
5.9%
서대구영상의학과의원 2
 
5.9%
참종합내과의원 1
 
2.9%
신세계연합의원 1
 
2.9%
Other values (9) 9
26.5%
2024-03-15T08:16:20.767747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 34
 
12.6%
의 31
 
11.5%
대 14
 
5.2%
병 12
 
4.4%
과 12
 
4.4%
구 11
 
4.1%
료 7
 
2.6%
합 6
 
2.2%
튼 6
 
2.2%
서 6
 
2.2%
Other values (54) 131
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 270
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 34
 
12.6%
의 31
 
11.5%
대 14
 
5.2%
병 12
 
4.4%
과 12
 
4.4%
구 11
 
4.1%
료 7
 
2.6%
합 6
 
2.2%
튼 6
 
2.2%
서 6
 
2.2%
Other values (54) 131
48.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 270
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 34
 
12.6%
의 31
 
11.5%
대 14
 
5.2%
병 12
 
4.4%
과 12
 
4.4%
구 11
 
4.1%
료 7
 
2.6%
합 6
 
2.2%
튼 6
 
2.2%
서 6
 
2.2%
Other values (54) 131
48.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 270
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 34
 
12.6%
의 31
 
11.5%
대 14
 
5.2%
병 12
 
4.4%
과 12
 
4.4%
구 11
 
4.1%
료 7
 
2.6%
합 6
 
2.2%
튼 6
 
2.2%
서 6
 
2.2%
Other values (54) 131
48.5%

의료기관소재지(도로명)
Text

Distinct19
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-03-15T08:16:21.540546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length33.5
Mean length28.882353
Min length22

Characters and Unicode

Total characters982
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)32.4%

Sample

1st row대구광역시 서구 국채보상로 200 (평리동)
2nd row대구광역시 서구 와룡로 307, 2층 208~221,224~225호 (중리동)
3rd row대구광역시 서구 와룡로 307, 2층 208~221,224~225호 (중리동)
4th row대구광역시 서구 달구벌대로 1691, 203호 (내당동)
5th row대구광역시 서구 달구벌대로 1691, 203호 (내당동)
ValueCountFrequency (%)
대구광역시 34
17.9%
서구 34
17.9%
내당동 11
 
5.8%
국채보상로 10
 
5.3%
평리동 10
 
5.3%
달구벌대로 9
 
4.7%
비산동 6
 
3.2%
중리동 6
 
3.2%
200 4
 
2.1%
2층 4
 
2.1%
Other values (38) 62
32.6%
2024-03-15T08:16:22.435618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
 
15.9%
구 79
 
8.0%
대 47
 
4.8%
2 41
 
4.2%
서 36
 
3.7%
( 34
 
3.5%
광 34
 
3.5%
역 34
 
3.5%
시 34
 
3.5%
) 34
 
3.5%
Other values (49) 453
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 542
55.2%
Decimal Number 181
 
18.4%
Space Separator 156
 
15.9%
Open Punctuation 34
 
3.5%
Close Punctuation 34
 
3.5%
Other Punctuation 24
 
2.4%
Math Symbol 11
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 79
14.6%
대 47
 
8.7%
서 36
 
6.6%
광 34
 
6.3%
역 34
 
6.3%
시 34
 
6.3%
동 34
 
6.3%
로 34
 
6.3%
리 19
 
3.5%
층 16
 
3.0%
Other values (34) 175
32.3%
Decimal Number
ValueCountFrequency (%)
2 41
22.7%
1 33
18.2%
0 23
12.7%
3 18
9.9%
7 18
9.9%
6 12
 
6.6%
9 11
 
6.1%
8 9
 
5.0%
5 9
 
5.0%
4 7
 
3.9%
Space Separator
ValueCountFrequency (%)
156
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 542
55.2%
Common 440
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 79
14.6%
대 47
 
8.7%
서 36
 
6.6%
광 34
 
6.3%
역 34
 
6.3%
시 34
 
6.3%
동 34
 
6.3%
로 34
 
6.3%
리 19
 
3.5%
층 16
 
3.0%
Other values (34) 175
32.3%
Common
ValueCountFrequency (%)
156
35.5%
2 41
 
9.3%
( 34
 
7.7%
) 34
 
7.7%
1 33
 
7.5%
, 24
 
5.5%
0 23
 
5.2%
3 18
 
4.1%
7 18
 
4.1%
6 12
 
2.7%
Other values (5) 47
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 542
55.2%
ASCII 440
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
35.5%
2 41
 
9.3%
( 34
 
7.7%
) 34
 
7.7%
1 33
 
7.5%
, 24
 
5.5%
0 23
 
5.2%
3 18
 
4.1%
7 18
 
4.1%
6 12
 
2.7%
Other values (5) 47
 
10.7%
Hangul
ValueCountFrequency (%)
구 79
14.6%
대 47
 
8.7%
서 36
 
6.6%
광 34
 
6.3%
역 34
 
6.3%
시 34
 
6.3%
동 34
 
6.3%
로 34
 
6.3%
리 19
 
3.5%
층 16
 
3.0%
Other values (34) 175
32.3%

자체병상수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.676471
Minimum0
Maximum445
Zeros12
Zeros (%)35.3%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T08:16:22.640989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24.5
Q3131
95-th percentile445
Maximum445
Range445
Interquartile range (IQR)131

Descriptive statistics

Standard deviation127.69488
Coefficient of variation (CV)1.4732358
Kurtosis3.6027318
Mean86.676471
Median Absolute Deviation (MAD)24.5
Skewness1.9907349
Sum2947
Variance16305.983
MonotonicityNot monotonic
2024-03-15T08:16:22.986075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 12
35.3%
147 4
 
11.8%
1 3
 
8.8%
131 3
 
8.8%
445 3
 
8.8%
99 3
 
8.8%
29 2
 
5.9%
151 1
 
2.9%
83 1
 
2.9%
19 1
 
2.9%
ValueCountFrequency (%)
0 12
35.3%
1 3
 
8.8%
19 1
 
2.9%
20 1
 
2.9%
29 2
 
5.9%
83 1
 
2.9%
99 3
 
8.8%
131 3
 
8.8%
147 4
 
11.8%
151 1
 
2.9%
ValueCountFrequency (%)
445 3
8.8%
151 1
 
2.9%
147 4
11.8%
131 3
8.8%
99 3
8.8%
83 1
 
2.9%
29 2
5.9%
20 1
 
2.9%
19 1
 
2.9%
1 3
8.8%

공동활용병상수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.264706
Minimum0
Maximum206
Zeros19
Zeros (%)55.9%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T08:16:23.338270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q397.5
95-th percentile200.7
Maximum206
Range206
Interquartile range (IQR)97.5

Descriptive statistics

Standard deviation74.484617
Coefficient of variation (CV)1.4529415
Kurtosis-0.035620636
Mean51.264706
Median Absolute Deviation (MAD)0
Skewness1.2050122
Sum1743
Variance5547.9581
MonotonicityNot monotonic
2024-03-15T08:16:23.689872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 19
55.9%
200 2
 
5.9%
59 2
 
5.9%
122 2
 
5.9%
9 1
 
2.9%
202 1
 
2.9%
206 1
 
2.9%
199 1
 
2.9%
29 1
 
2.9%
72 1
 
2.9%
Other values (3) 3
 
8.8%
ValueCountFrequency (%)
0 19
55.9%
9 1
 
2.9%
29 1
 
2.9%
40 1
 
2.9%
59 2
 
5.9%
72 1
 
2.9%
106 1
 
2.9%
118 1
 
2.9%
122 2
 
5.9%
199 1
 
2.9%
ValueCountFrequency (%)
206 1
2.9%
202 1
2.9%
200 2
5.9%
199 1
2.9%
122 2
5.9%
118 1
2.9%
106 1
2.9%
72 1
2.9%
59 2
5.9%
40 1
2.9%

총병상수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.94118
Minimum0
Maximum445
Zeros10
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-03-15T08:16:24.032762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median158
Q3204.5
95-th percentile445
Maximum445
Range445
Interquartile range (IQR)204.5

Descriptive statistics

Standard deviation133.14288
Coefficient of variation (CV)0.96521491
Kurtosis0.32158321
Mean137.94118
Median Absolute Deviation (MAD)96
Skewness0.80193025
Sum4690
Variance17727.027
MonotonicityNot monotonic
2024-03-15T08:16:24.399588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 10
29.4%
206 3
 
8.8%
201 3
 
8.8%
445 3
 
8.8%
29 2
 
5.9%
221 2
 
5.9%
147 1
 
2.9%
20 1
 
2.9%
19 1
 
2.9%
131 1
 
2.9%
Other values (7) 7
20.6%
ValueCountFrequency (%)
0 10
29.4%
19 1
 
2.9%
20 1
 
2.9%
29 2
 
5.9%
131 1
 
2.9%
147 1
 
2.9%
156 1
 
2.9%
160 1
 
2.9%
191 1
 
2.9%
200 1
 
2.9%
ValueCountFrequency (%)
445 3
8.8%
221 2
5.9%
206 3
8.8%
205 1
 
2.9%
203 1
 
2.9%
202 1
 
2.9%
201 3
8.8%
200 1
 
2.9%
191 1
 
2.9%
160 1
 
2.9%

의료장비종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size400.0 B
유방촬영용장치
13 
MRI
11 
CT
10 

Length

Max length7
Median length3
Mean length4.2352941
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCT
2nd rowMRI
3rd rowCT
4th rowMRI
5th rowCT

Common Values

ValueCountFrequency (%)
유방촬영용장치 13
38.2%
MRI 11
32.4%
CT 10
29.4%

Length

2024-03-15T08:16:24.940498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:16:25.283465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유방촬영용장치 13
38.2%
mri 11
32.4%
ct 10
29.4%

공동이용여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
19 
True
15 
ValueCountFrequency (%)
False 19
55.9%
True 15
44.1%
2024-03-15T08:16:25.677688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

모델명
Text

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-03-15T08:16:26.600065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length35
Mean length18.058824
Min length5

Characters and Unicode

Total characters614
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)79.4%

Sample

1st rowSOMATOM go.All
2nd rowMAGNETOM Lumina
3rd rowSOMATOM go.Top
4th rowSigna 1.5T Excite HD Magnetic Resonanace Systems
5th rowBrivo CT 385
ValueCountFrequency (%)
somatom 8
 
9.5%
magnetom 6
 
7.1%
signa 4
 
4.8%
system 3
 
3.6%
essenza 3
 
3.6%
1.5t 3
 
3.6%
emotion 2
 
2.4%
configuration 2
 
2.4%
senographe 2
 
2.4%
mx-300 2
 
2.4%
Other values (46) 49
58.3%
2024-03-15T08:16:27.951652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
8.1%
M 39
 
6.4%
i 33
 
5.4%
e 31
 
5.0%
n 27
 
4.4%
S 26
 
4.2%
T 25
 
4.1%
A 25
 
4.1%
O 24
 
3.9%
a 24
 
3.9%
Other values (48) 310
50.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 278
45.3%
Uppercase Letter 227
37.0%
Space Separator 50
 
8.1%
Decimal Number 39
 
6.4%
Dash Punctuation 11
 
1.8%
Other Punctuation 8
 
1.3%
Math Symbol 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 33
11.9%
e 31
11.2%
n 27
9.7%
a 24
 
8.6%
s 22
 
7.9%
o 22
 
7.9%
t 22
 
7.9%
g 13
 
4.7%
m 12
 
4.3%
r 11
 
4.0%
Other values (13) 61
21.9%
Uppercase Letter
ValueCountFrequency (%)
M 39
17.2%
S 26
11.5%
T 25
11.0%
A 25
11.0%
O 24
10.6%
E 21
9.3%
N 10
 
4.4%
G 10
 
4.4%
R 8
 
3.5%
D 7
 
3.1%
Other values (9) 32
14.1%
Decimal Number
ValueCountFrequency (%)
0 14
35.9%
1 6
15.4%
5 6
15.4%
3 4
 
10.3%
6 4
 
10.3%
8 2
 
5.1%
7 1
 
2.6%
4 1
 
2.6%
2 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 5
62.5%
/ 1
 
12.5%
; 1
 
12.5%
& 1
 
12.5%
Space Separator
ValueCountFrequency (%)
50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 505
82.2%
Common 109
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 39
 
7.7%
i 33
 
6.5%
e 31
 
6.1%
n 27
 
5.3%
S 26
 
5.1%
T 25
 
5.0%
A 25
 
5.0%
O 24
 
4.8%
a 24
 
4.8%
s 22
 
4.4%
Other values (32) 229
45.3%
Common
ValueCountFrequency (%)
50
45.9%
0 14
 
12.8%
- 11
 
10.1%
1 6
 
5.5%
5 6
 
5.5%
. 5
 
4.6%
3 4
 
3.7%
6 4
 
3.7%
8 2
 
1.8%
7 1
 
0.9%
Other values (6) 6
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 614
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
 
8.1%
M 39
 
6.4%
i 33
 
5.4%
e 31
 
5.0%
n 27
 
4.4%
S 26
 
4.2%
T 25
 
4.1%
A 25
 
4.1%
O 24
 
3.9%
a 24
 
3.9%
Other values (48) 310
50.5%

형식명
Text

Distinct25
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-03-15T08:16:28.780111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length9.2058824
Min length1

Characters and Unicode

Total characters313
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)52.9%

Sample

1st rowWCT-625-140
2nd row3
3rd rowWCT-825-140
4th row1.5T
5th rowWCT-200-140
ValueCountFrequency (%)
wct-180-130 3
 
7.9%
m-1.5-s 3
 
7.9%
mr-85-35 2
 
5.3%
1.5t 2
 
5.3%
mr-100-39 2
 
5.3%
wct-345-130 2
 
5.3%
mhr-35-p 2
 
5.3%
mhr-200-49 1
 
2.6%
mri 1
 
2.6%
system 1
 
2.6%
Other values (19) 19
50.0%
2024-03-15T08:16:29.935124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.6%
0 32
 
10.2%
1 24
 
7.7%
M 20
 
6.4%
5 20
 
6.4%
3 19
 
6.1%
T 15
 
4.8%
R 15
 
4.8%
4 11
 
3.5%
W 10
 
3.2%
Other values (30) 95
30.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 122
39.0%
Uppercase Letter 118
37.7%
Dash Punctuation 52
16.6%
Lowercase Letter 10
 
3.2%
Other Punctuation 6
 
1.9%
Space Separator 4
 
1.3%
Math Symbol 1
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 20
16.9%
T 15
12.7%
R 15
12.7%
W 10
8.5%
C 10
8.5%
S 9
7.6%
A 8
 
6.8%
H 7
 
5.9%
E 6
 
5.1%
N 4
 
3.4%
Other values (8) 14
11.9%
Decimal Number
ValueCountFrequency (%)
0 32
26.2%
1 24
19.7%
5 20
16.4%
3 19
15.6%
4 11
 
9.0%
8 7
 
5.7%
2 4
 
3.3%
9 4
 
3.3%
6 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
t 2
20.0%
m 1
10.0%
e 1
10.0%
s 1
10.0%
y 1
10.0%
o 1
10.0%
n 1
10.0%
a 1
10.0%
v 1
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 185
59.1%
Latin 128
40.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 20
15.6%
T 15
11.7%
R 15
11.7%
W 10
7.8%
C 10
7.8%
S 9
 
7.0%
A 8
 
6.2%
H 7
 
5.5%
E 6
 
4.7%
N 4
 
3.1%
Other values (17) 24
18.8%
Common
ValueCountFrequency (%)
- 52
28.1%
0 32
17.3%
1 24
13.0%
5 20
 
10.8%
3 19
 
10.3%
4 11
 
5.9%
8 7
 
3.8%
. 6
 
3.2%
4
 
2.2%
2 4
 
2.2%
Other values (3) 6
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 313
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.6%
0 32
 
10.2%
1 24
 
7.7%
M 20
 
6.4%
5 20
 
6.4%
3 19
 
6.1%
T 15
 
4.8%
R 15
 
4.8%
4 11
 
3.5%
W 10
 
3.2%
Other values (30) 95
30.4%

Interactions

2024-03-15T08:16:16.956905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:14.453279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:15.205421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:16.038524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:17.202273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:14.639274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:15.452568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:16.271563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:17.433071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:14.787668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:15.680507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:16.502420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:17.665703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:14.963754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:15.902599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:16:16.728357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:16:30.111229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번의료기관명의료기관소재지(도로명)자체병상수공동활용병상수총병상수의료장비종류공동이용여부모델명형식명
순번1.0000.6110.6110.0000.6540.4910.6990.8820.9610.773
의료기관명0.6111.0001.0001.0000.7810.7380.0000.7530.9290.525
의료기관소재지(도로명)0.6111.0001.0001.0000.7810.7380.0000.7530.9290.525
자체병상수0.0001.0001.0001.0000.6140.9170.0000.4360.8990.898
공동활용병상수0.6540.7810.7810.6141.0000.5200.8250.9940.6720.000
총병상수0.4910.7380.7380.9170.5201.0000.5360.8310.9980.915
의료장비종류0.6990.0000.0000.0000.8250.5361.0000.4511.0001.000
공동이용여부0.8820.7530.7530.4360.9940.8310.4511.0000.9010.580
모델명0.9610.9290.9290.8990.6720.9981.0000.9011.0000.992
형식명0.7730.5250.5250.8980.0000.9151.0000.5800.9921.000
2024-03-15T08:16:30.322975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공동이용여부의료장비종류
공동이용여부1.0000.687
의료장비종류0.6871.000
2024-03-15T08:16:30.527928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번자체병상수공동활용병상수총병상수의료장비종류공동이용여부
순번1.000-0.161-0.733-0.4790.4830.617
자체병상수-0.1611.0000.1060.7160.0000.502
공동활용병상수-0.7330.1061.0000.5980.4820.871
총병상수-0.4790.7160.5981.0000.4570.908
의료장비종류0.4830.0000.4820.4571.0000.687
공동이용여부0.6170.5020.8710.9080.6871.000

Missing values

2024-03-15T08:16:17.998760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:16:18.522072image/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

순번의료기관명의료기관소재지(도로명)자체병상수공동활용병상수총병상수의료장비종류공동이용여부모델명형식명
01대명의료재단서대구병원대구광역시 서구 국채보상로 200 (평리동)1479156CTYSOMATOM go.AllWCT-625-140
12디케어센터의원대구광역시 서구 와룡로 307, 2층 208~221,224~225호 (중리동)0202202MRIYMAGNETOM Lumina3
23디케어센터의원대구광역시 서구 와룡로 307, 2층 208~221,224~225호 (중리동)0206206CTYSOMATOM go.TopWCT-825-140
34네이처영상의학과의원대구광역시 서구 달구벌대로 1691, 203호 (내당동)1200201MRIYSigna 1.5T Excite HD Magnetic Resonanace Systems1.5T
45네이처영상의학과의원대구광역시 서구 달구벌대로 1691, 203호 (내당동)1199200CTYBrivo CT 385WCT-200-140
56네이처영상의학과의원대구광역시 서구 달구벌대로 1691, 203호 (내당동)1200201MRIYSIGNA PioneerM-3.0-S
67새동산병원대구광역시 서구 국채보상로 379 (비산동)13129160CTYSOMATOM ScopeWCT-180-130
78새동산병원대구광역시 서구 국채보상로 379 (비산동)13172203MRIYMAGNETOM Sempra1.5T
89대구의료원대구광역시 서구 평리로 157 (중리동)4450445CTNSOMATOM Definition EdgeWCT-800-140
910대명의료재단서대구병원대구광역시 서구 국채보상로 200 (평리동)14759206MRIYMAGNETOM EssenzaESSENZA
순번의료기관명의료기관소재지(도로명)자체병상수공동활용병상수총병상수의료장비종류공동이용여부모델명형식명
2425신세계연합의원대구광역시 서구 북비산로 360 (비산동)000유방촬영용장치NSENOGRAPHE DMR+SENOGRAPHE DMR+
2526대구의료원대구광역시 서구 평리로 157 (중리동)4450445유방촬영용장치NSelenia Dimensions SystemMHR-200-49
2627더편한속연합내과의원대구광역시 서구 국채보상로 262, 2,3층 (평리동)000유방촬영용장치NAffinity Mammography System & AccessoriesMR-100-39
2728인구보건복지협회가족보건의원대구광역시 서구 국채보상로46길 16 (평리동)000유방촬영용장치NDMX-600MR-100-39
2829새동산병원대구광역시 서구 국채보상로 379 (비산동)1310131유방촬영용장치NSENOGRAPHE-700T/800TMR-100-35
2930아세아연합의원대구광역시 서구 서대구로 49, 지하1층,2층~3층 (내당동)19019유방촬영용장치NMF-150MR-150-35
3031인구보건복지협회가족보건의원대구광역시 서구 국채보상로46길 16 (평리동)000유방촬영용장치NMX-300MR-85-35
3132참종합내과의원대구광역시 서구 문화로49길 31 (평리동)000유방촬영용장치NMX-300MR-85-35
3233현대연합의원대구광역시 서구 팔달로 160 (비산동)20020유방촬영용장치NHF-46MHR-35-P
3334대명의료재단서대구병원대구광역시 서구 국채보상로 200 (평리동)1470147유방촬영용장치NMXR-200MMHR-49-P