Overview

Dataset statistics

Number of variables49
Number of observations30
Missing cells120
Missing cells (%)8.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory444.4 B

Variable types

Numeric44
Categorical1
Unsupported4

Dataset

Description안질환 환자의 RNFL두께와 평균 시신경유두비, 수직 시신경유두비, ETDRS 중심 평균 두께, ETDRS 3mm  zone (상측, 하측, 이측,비측) 평균 두께, ETDRS 6mm  zone (상측, 하측, 이측,비측)평균 두께
Author가톨릭대학교 서울성모병원
URLhttp://cmcdata.net/data/dataset/rnfl-etdrs

Alerts

AV_CD_R_R has 30 (100.0%) missing valuesMissing
AV_CD_R_L has 30 (100.0%) missing valuesMissing
VE_CD_R_R has 30 (100.0%) missing valuesMissing
VE_CD_R_L has 30 (100.0%) missing valuesMissing
PatID has unique valuesUnique
RNFL_T_12_R has unique valuesUnique
RNFL_T_12_L has unique valuesUnique
RNFL_T_1_R has unique valuesUnique
RNFL_T_1_L has unique valuesUnique
RNFL_T_2_R has unique valuesUnique
RNFL_T_2_L has unique valuesUnique
RNFL_T_3_R has unique valuesUnique
RNFL_T_3_L has unique valuesUnique
RNFL_T_4_R has unique valuesUnique
RNFL_T_4_L has unique valuesUnique
RNFL_T_5_R has unique valuesUnique
RNFL_T_5_L has unique valuesUnique
RNFL_T_6_R has unique valuesUnique
RNFL_T_6_L has unique valuesUnique
RNFL_T_7_R has unique valuesUnique
RNFL_T_7_L has unique valuesUnique
RNFL_T_8_R has unique valuesUnique
RNFL_T_8_L has unique valuesUnique
RNFL_T_9_R has unique valuesUnique
RNFL_T_9_L has unique valuesUnique
RNFL_T_10_R has unique valuesUnique
RNFL_T_10_L has unique valuesUnique
RNFL_T_11_R has unique valuesUnique
RNFL_T_11_L has unique valuesUnique
CMT_ETDRS_R has unique valuesUnique
CMT_ETDRS_L has unique valuesUnique
SMT_3_R has unique valuesUnique
SMT_3_L has unique valuesUnique
IMT_3_R has unique valuesUnique
IMT_3_L has unique valuesUnique
TMT_3_R has unique valuesUnique
TMT_3_L has unique valuesUnique
NMT_3_R has unique valuesUnique
NMT_3_L has unique valuesUnique
SMT_6_R has unique valuesUnique
SMT_6_L has unique valuesUnique
IMT_6_R has unique valuesUnique
IMT_6_L has unique valuesUnique
TMT_6_R has unique valuesUnique
TMT_6_L has unique valuesUnique
NMT_6_R has unique valuesUnique
NMT_6_L has unique valuesUnique
AV_CD_R_R is an unsupported type, check if it needs cleaning or further analysisUnsupported
AV_CD_R_L is an unsupported type, check if it needs cleaning or further analysisUnsupported
VE_CD_R_R is an unsupported type, check if it needs cleaning or further analysisUnsupported
VE_CD_R_L is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-10-08 18:56:34.136735
Analysis finished2023-10-08 18:56:35.329074
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

PatID
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:35.640867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-10-09T03:56:36.042287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

sex
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
F
19 
M
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowF
4th rowM
5th rowM

Common Values

ValueCountFrequency (%)
F 19
63.3%
M 11
36.7%

Length

2023-10-09T03:56:36.411065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-09T03:56:36.904450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 19
63.3%
m 11
36.7%

age_oct
Real number (ℝ)

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.2
Minimum29
Maximum83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:37.121557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile38.9
Q151.5
median62.5
Q368.75
95-th percentile77.55
Maximum83
Range54
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation12.745249
Coefficient of variation (CV)0.2117151
Kurtosis-0.08184761
Mean60.2
Median Absolute Deviation (MAD)8.5
Skewness-0.51181177
Sum1806
Variance162.44138
MonotonicityNot monotonic
2023-10-09T03:56:37.408545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
66 2
 
6.7%
55 2
 
6.7%
51 2
 
6.7%
71 2
 
6.7%
68 2
 
6.7%
48 1
 
3.3%
53 1
 
3.3%
60 1
 
3.3%
54 1
 
3.3%
62 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
29 1
3.3%
38 1
3.3%
40 1
3.3%
44 1
3.3%
48 1
3.3%
49 1
3.3%
51 2
6.7%
53 1
3.3%
54 1
3.3%
55 2
6.7%
ValueCountFrequency (%)
83 1
3.3%
78 1
3.3%
77 1
3.3%
74 1
3.3%
71 2
6.7%
70 1
3.3%
69 1
3.3%
68 2
6.7%
67 1
3.3%
66 2
6.7%

RNFL_T_12_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.466667
Minimum66
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:38.009655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile72.9
Q184.25
median99.5
Q3114.25
95-th percentile123.1
Maximum125
Range59
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.947689
Coefficient of variation (CV)0.18227172
Kurtosis-1.2603796
Mean98.466667
Median Absolute Deviation (MAD)15.5
Skewness-0.14692626
Sum2954
Variance322.11954
MonotonicityNot monotonic
2023-10-09T03:56:38.319894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
75 1
 
3.3%
124 1
 
3.3%
111 1
 
3.3%
66 1
 
3.3%
115 1
 
3.3%
103 1
 
3.3%
122 1
 
3.3%
121 1
 
3.3%
72 1
 
3.3%
101 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
66 1
3.3%
72 1
3.3%
74 1
3.3%
75 1
3.3%
76 1
3.3%
77 1
3.3%
79 1
3.3%
84 1
3.3%
85 1
3.3%
86 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
124 1
3.3%
122 1
3.3%
121 1
3.3%
120 1
3.3%
118 1
3.3%
116 1
3.3%
115 1
3.3%
112 1
3.3%
111 1
3.3%

RNFL_T_12_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.033333
Minimum66
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:38.522895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile70.9
Q180.25
median87.5
Q3101.75
95-th percentile114.75
Maximum121
Range55
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation14.97235
Coefficient of variation (CV)0.16447107
Kurtosis-0.91105445
Mean91.033333
Median Absolute Deviation (MAD)12.5
Skewness0.25195343
Sum2731
Variance224.17126
MonotonicityNot monotonic
2023-10-09T03:56:38.818677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
101 1
 
3.3%
78 1
 
3.3%
84 1
 
3.3%
82 1
 
3.3%
111 1
 
3.3%
112 1
 
3.3%
80 1
 
3.3%
110 1
 
3.3%
104 1
 
3.3%
98 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
66 1
3.3%
70 1
3.3%
72 1
3.3%
73 1
3.3%
74 1
3.3%
75 1
3.3%
78 1
3.3%
80 1
3.3%
81 1
3.3%
82 1
3.3%
ValueCountFrequency (%)
121 1
3.3%
117 1
3.3%
112 1
3.3%
111 1
3.3%
110 1
3.3%
104 1
3.3%
103 1
3.3%
102 1
3.3%
101 1
3.3%
100 1
3.3%

RNFL_T_1_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.533333
Minimum66
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:39.146249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile69.25
Q183.25
median95.5
Q3108.75
95-th percentile121.55
Maximum124
Range58
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation17.274125
Coefficient of variation (CV)0.18081778
Kurtosis-1.0579173
Mean95.533333
Median Absolute Deviation (MAD)13
Skewness0.042804529
Sum2866
Variance298.3954
MonotonicityNot monotonic
2023-10-09T03:56:39.425429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
106 1
 
3.3%
85 1
 
3.3%
110 1
 
3.3%
108 1
 
3.3%
96 1
 
3.3%
82 1
 
3.3%
72 1
 
3.3%
87 1
 
3.3%
102 1
 
3.3%
120 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
66 1
3.3%
67 1
3.3%
72 1
3.3%
74 1
3.3%
75 1
3.3%
78 1
3.3%
82 1
3.3%
83 1
3.3%
84 1
3.3%
85 1
3.3%
ValueCountFrequency (%)
124 1
3.3%
122 1
3.3%
121 1
3.3%
120 1
3.3%
119 1
3.3%
114 1
3.3%
110 1
3.3%
109 1
3.3%
108 1
3.3%
106 1
3.3%

RNFL_T_1_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.7
Minimum65
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:39.683493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.9
Q175
median91
Q3102.5
95-th percentile119.55
Maximum124
Range59
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation17.216972
Coefficient of variation (CV)0.18982329
Kurtosis-0.91862799
Mean90.7
Median Absolute Deviation (MAD)13
Skewness0.20614898
Sum2721
Variance296.42414
MonotonicityNot monotonic
2023-10-09T03:56:40.081131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
70 1
 
3.3%
78 1
 
3.3%
113 1
 
3.3%
104 1
 
3.3%
68 1
 
3.3%
120 1
 
3.3%
107 1
 
3.3%
71 1
 
3.3%
69 1
 
3.3%
94 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
68 1
3.3%
69 1
3.3%
70 1
3.3%
71 1
3.3%
72 1
3.3%
74 1
3.3%
78 1
3.3%
81 1
3.3%
ValueCountFrequency (%)
124 1
3.3%
120 1
3.3%
119 1
3.3%
113 1
3.3%
110 1
3.3%
107 1
3.3%
104 1
3.3%
103 1
3.3%
101 1
3.3%
99 1
3.3%

RNFL_T_2_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.533333
Minimum65
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:40.491195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile67.9
Q181.25
median97.5
Q3109.75
95-th percentile121.55
Maximum125
Range60
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation17.703951
Coefficient of variation (CV)0.185317
Kurtosis-1.1135818
Mean95.533333
Median Absolute Deviation (MAD)15
Skewness-0.094717058
Sum2866
Variance313.42989
MonotonicityNot monotonic
2023-10-09T03:56:40.867567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
91 1
 
3.3%
110 1
 
3.3%
98 1
 
3.3%
65 1
 
3.3%
75 1
 
3.3%
104 1
 
3.3%
78 1
 
3.3%
82 1
 
3.3%
121 1
 
3.3%
108 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
67 1
3.3%
69 1
3.3%
71 1
3.3%
75 1
3.3%
78 1
3.3%
79 1
3.3%
81 1
3.3%
82 1
3.3%
86 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
122 1
3.3%
121 1
3.3%
118 1
3.3%
114 1
3.3%
113 1
3.3%
112 1
3.3%
110 1
3.3%
109 1
3.3%
108 1
3.3%

RNFL_T_2_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.233333
Minimum65
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:41.272238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile67.8
Q180.25
median96
Q3106.75
95-th percentile118.75
Maximum124
Range59
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation16.829128
Coefficient of variation (CV)0.17858997
Kurtosis-1.0043385
Mean94.233333
Median Absolute Deviation (MAD)14
Skewness-0.081534992
Sum2827
Variance283.21954
MonotonicityNot monotonic
2023-10-09T03:56:41.552725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
77 1
 
3.3%
97 1
 
3.3%
102 1
 
3.3%
121 1
 
3.3%
112 1
 
3.3%
66 1
 
3.3%
108 1
 
3.3%
116 1
 
3.3%
103 1
 
3.3%
99 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
70 1
3.3%
72 1
3.3%
74 1
3.3%
77 1
3.3%
79 1
3.3%
80 1
3.3%
81 1
3.3%
83 1
3.3%
ValueCountFrequency (%)
124 1
3.3%
121 1
3.3%
116 1
3.3%
115 1
3.3%
114 1
3.3%
112 1
3.3%
108 1
3.3%
107 1
3.3%
106 1
3.3%
103 1
3.3%

RNFL_T_3_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.333333
Minimum65
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:41.782585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile67.45
Q178.75
median96.5
Q3110.75
95-th percentile123.55
Maximum125
Range60
Interquartile range (IQR)32

Descriptive statistics

Standard deviation19.117303
Coefficient of variation (CV)0.20053115
Kurtosis-1.2540197
Mean95.333333
Median Absolute Deviation (MAD)15.5
Skewness-0.033566579
Sum2860
Variance365.47126
MonotonicityNot monotonic
2023-10-09T03:56:42.005394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
99 1
 
3.3%
123 1
 
3.3%
91 1
 
3.3%
73 1
 
3.3%
85 1
 
3.3%
119 1
 
3.3%
76 1
 
3.3%
122 1
 
3.3%
94 1
 
3.3%
113 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
67 1
3.3%
68 1
3.3%
69 1
3.3%
72 1
3.3%
73 1
3.3%
76 1
3.3%
78 1
3.3%
81 1
3.3%
85 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
124 1
3.3%
123 1
3.3%
122 1
3.3%
119 1
3.3%
113 1
3.3%
112 1
3.3%
111 1
3.3%
110 1
3.3%
109 1
3.3%

RNFL_T_3_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97
Minimum65
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:42.259417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.45
Q186.25
median99.5
Q3113.25
95-th percentile121.55
Maximum125
Range60
Interquartile range (IQR)27

Descriptive statistics

Standard deviation18.935462
Coefficient of variation (CV)0.19521095
Kurtosis-1.1142203
Mean97
Median Absolute Deviation (MAD)14
Skewness-0.29992674
Sum2910
Variance358.55172
MonotonicityNot monotonic
2023-10-09T03:56:42.482443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
122 1
 
3.3%
86 1
 
3.3%
93 1
 
3.3%
66 1
 
3.3%
72 1
 
3.3%
98 1
 
3.3%
68 1
 
3.3%
115 1
 
3.3%
87 1
 
3.3%
67 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
67 1
3.3%
68 1
3.3%
72 1
3.3%
74 1
3.3%
75 1
3.3%
86 1
3.3%
87 1
3.3%
89 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
122 1
3.3%
121 1
3.3%
120 1
3.3%
119 1
3.3%
118 1
3.3%
115 1
3.3%
114 1
3.3%
111 1
3.3%
109 1
3.3%

RNFL_T_4_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.466667
Minimum65
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:42.913748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.45
Q178.25
median96.5
Q3109.75
95-th percentile122.1
Maximum125
Range60
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation18.641321
Coefficient of variation (CV)0.19526523
Kurtosis-1.2044206
Mean95.466667
Median Absolute Deviation (MAD)16.5
Skewness-0.18457116
Sum2864
Variance347.49885
MonotonicityNot monotonic
2023-10-09T03:56:43.186437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
125 1
 
3.3%
110 1
 
3.3%
108 1
 
3.3%
94 1
 
3.3%
101 1
 
3.3%
109 1
 
3.3%
106 1
 
3.3%
87 1
 
3.3%
71 1
 
3.3%
67 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
67 1
3.3%
69 1
3.3%
71 1
3.3%
75 1
3.3%
77 1
3.3%
78 1
3.3%
79 1
3.3%
87 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
123 1
3.3%
121 1
3.3%
117 1
3.3%
116 1
3.3%
114 1
3.3%
112 1
3.3%
110 1
3.3%
109 1
3.3%
108 1
3.3%

RNFL_T_4_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.933333
Minimum67
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:43.419237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile70.7
Q182.25
median99
Q3109.75
95-th percentile123.55
Maximum125
Range58
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation17.57336
Coefficient of variation (CV)0.18129326
Kurtosis-1.2072646
Mean96.933333
Median Absolute Deviation (MAD)15.5
Skewness-0.062364154
Sum2908
Variance308.82299
MonotonicityNot monotonic
2023-10-09T03:56:43.689033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
124 1
 
3.3%
123 1
 
3.3%
82 1
 
3.3%
86 1
 
3.3%
77 1
 
3.3%
78 1
 
3.3%
84 1
 
3.3%
114 1
 
3.3%
83 1
 
3.3%
68 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
67 1
3.3%
68 1
3.3%
74 1
3.3%
75 1
3.3%
77 1
3.3%
78 1
3.3%
79 1
3.3%
82 1
3.3%
83 1
3.3%
84 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
124 1
3.3%
123 1
3.3%
118 1
3.3%
117 1
3.3%
115 1
3.3%
114 1
3.3%
110 1
3.3%
109 1
3.3%
108 1
3.3%

RNFL_T_5_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.266667
Minimum65
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:43.957810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile69.45
Q182.25
median98
Q3109.75
95-th percentile120.65
Maximum124
Range59
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation16.89916
Coefficient of variation (CV)0.17554529
Kurtosis-1.032238
Mean96.266667
Median Absolute Deviation (MAD)13.5
Skewness-0.22993912
Sum2888
Variance285.58161
MonotonicityNot monotonic
2023-10-09T03:56:44.210323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
111 1
 
3.3%
74 1
 
3.3%
69 1
 
3.3%
65 1
 
3.3%
80 1
 
3.3%
100 1
 
3.3%
91 1
 
3.3%
75 1
 
3.3%
115 1
 
3.3%
83 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
69 1
3.3%
70 1
3.3%
74 1
3.3%
75 1
3.3%
77 1
3.3%
80 1
3.3%
82 1
3.3%
83 1
3.3%
88 1
3.3%
ValueCountFrequency (%)
124 1
3.3%
122 1
3.3%
119 1
3.3%
115 1
3.3%
113 1
3.3%
112 1
3.3%
111 1
3.3%
110 1
3.3%
109 1
3.3%
108 1
3.3%

RNFL_T_5_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.966667
Minimum67
Maximum123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:44.752891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile68.45
Q176.25
median93.5
Q3104.75
95-th percentile120.2
Maximum123
Range56
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation17.066772
Coefficient of variation (CV)0.18557563
Kurtosis-1.1021859
Mean91.966667
Median Absolute Deviation (MAD)15
Skewness0.14093994
Sum2759
Variance291.27471
MonotonicityNot monotonic
2023-10-09T03:56:45.179411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
87 1
 
3.3%
70 1
 
3.3%
98 1
 
3.3%
78 1
 
3.3%
105 1
 
3.3%
75 1
 
3.3%
95 1
 
3.3%
104 1
 
3.3%
118 1
 
3.3%
100 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
67 1
3.3%
68 1
3.3%
69 1
3.3%
70 1
3.3%
71 1
3.3%
73 1
3.3%
75 1
3.3%
76 1
3.3%
77 1
3.3%
78 1
3.3%
ValueCountFrequency (%)
123 1
3.3%
122 1
3.3%
118 1
3.3%
112 1
3.3%
111 1
3.3%
108 1
3.3%
107 1
3.3%
105 1
3.3%
104 1
3.3%
102 1
3.3%

RNFL_T_6_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.333333
Minimum65
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:45.574646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.45
Q178.5
median93.5
Q3108.75
95-th percentile118.1
Maximum121
Range56
Interquartile range (IQR)30.25

Descriptive statistics

Standard deviation17.860249
Coefficient of variation (CV)0.19135981
Kurtosis-1.2269414
Mean93.333333
Median Absolute Deviation (MAD)15.5
Skewness-0.14514339
Sum2800
Variance318.98851
MonotonicityNot monotonic
2023-10-09T03:56:45.792259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
93 1
 
3.3%
92 1
 
3.3%
73 1
 
3.3%
115 1
 
3.3%
117 1
 
3.3%
91 1
 
3.3%
69 1
 
3.3%
96 1
 
3.3%
80 1
 
3.3%
108 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
67 1
3.3%
68 1
3.3%
69 1
3.3%
72 1
3.3%
73 1
3.3%
78 1
3.3%
80 1
3.3%
86 1
3.3%
ValueCountFrequency (%)
121 1
3.3%
119 1
3.3%
117 1
3.3%
115 1
3.3%
114 1
3.3%
113 1
3.3%
112 1
3.3%
109 1
3.3%
108 1
3.3%
105 1
3.3%

RNFL_T_6_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.033333
Minimum65
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:46.042491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.45
Q179.25
median92.5
Q3105.5
95-th percentile120.4
Maximum125
Range60
Interquartile range (IQR)26.25

Descriptive statistics

Standard deviation17.020238
Coefficient of variation (CV)0.18294774
Kurtosis-0.86771718
Mean93.033333
Median Absolute Deviation (MAD)13.5
Skewness0.11402356
Sum2791
Variance289.68851
MonotonicityNot monotonic
2023-10-09T03:56:46.259543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
114 1
 
3.3%
100 1
 
3.3%
73 1
 
3.3%
108 1
 
3.3%
79 1
 
3.3%
104 1
 
3.3%
88 1
 
3.3%
102 1
 
3.3%
74 1
 
3.3%
67 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
67 1
3.3%
73 1
3.3%
74 1
3.3%
77 1
3.3%
78 1
3.3%
79 1
3.3%
80 1
3.3%
81 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
124 1
3.3%
116 1
3.3%
114 1
3.3%
112 1
3.3%
111 1
3.3%
108 1
3.3%
106 1
3.3%
104 1
3.3%
102 1
3.3%

RNFL_T_7_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.7
Minimum67
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:46.462400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile68.45
Q178
median96.5
Q3109.25
95-th percentile122.1
Maximum124
Range57
Interquartile range (IQR)31.25

Descriptive statistics

Standard deviation17.975366
Coefficient of variation (CV)0.18981379
Kurtosis-1.2352061
Mean94.7
Median Absolute Deviation (MAD)15
Skewness0.043593103
Sum2841
Variance323.11379
MonotonicityNot monotonic
2023-10-09T03:56:46.786206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
121 1
 
3.3%
75 1
 
3.3%
72 1
 
3.3%
111 1
 
3.3%
84 1
 
3.3%
96 1
 
3.3%
105 1
 
3.3%
119 1
 
3.3%
98 1
 
3.3%
81 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
67 1
3.3%
68 1
3.3%
69 1
3.3%
72 1
3.3%
74 1
3.3%
75 1
3.3%
76 1
3.3%
77 1
3.3%
81 1
3.3%
83 1
3.3%
ValueCountFrequency (%)
124 1
3.3%
123 1
3.3%
121 1
3.3%
119 1
3.3%
116 1
3.3%
115 1
3.3%
111 1
3.3%
110 1
3.3%
107 1
3.3%
105 1
3.3%

RNFL_T_7_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.9
Minimum65
Maximum123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:47.038346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.45
Q178.75
median94.5
Q3106.75
95-th percentile120.1
Maximum123
Range58
Interquartile range (IQR)28

Descriptive statistics

Standard deviation17.742118
Coefficient of variation (CV)0.19098082
Kurtosis-1.0729354
Mean92.9
Median Absolute Deviation (MAD)14
Skewness-0.01187021
Sum2787
Variance314.78276
MonotonicityNot monotonic
2023-10-09T03:56:47.293222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
123 1
 
3.3%
78 1
 
3.3%
121 1
 
3.3%
85 1
 
3.3%
119 1
 
3.3%
91 1
 
3.3%
92 1
 
3.3%
87 1
 
3.3%
67 1
 
3.3%
65 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
67 1
3.3%
68 1
3.3%
70 1
3.3%
72 1
3.3%
75 1
3.3%
78 1
3.3%
81 1
3.3%
83 1
3.3%
ValueCountFrequency (%)
123 1
3.3%
121 1
3.3%
119 1
3.3%
118 1
3.3%
112 1
3.3%
110 1
3.3%
109 1
3.3%
107 1
3.3%
106 1
3.3%
103 1
3.3%

RNFL_T_8_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.466667
Minimum65
Maximum123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:47.578530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile67.8
Q183.75
median95
Q3111
95-th percentile120.65
Maximum123
Range58
Interquartile range (IQR)27.25

Descriptive statistics

Standard deviation17.270132
Coefficient of variation (CV)0.18090222
Kurtosis-1.0050985
Mean95.466667
Median Absolute Deviation (MAD)14.5
Skewness-0.083591959
Sum2864
Variance298.25747
MonotonicityNot monotonic
2023-10-09T03:56:47.830990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
103 1
 
3.3%
117 1
 
3.3%
78 1
 
3.3%
97 1
 
3.3%
88 1
 
3.3%
94 1
 
3.3%
66 1
 
3.3%
79 1
 
3.3%
114 1
 
3.3%
65 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
70 1
3.3%
71 1
3.3%
77 1
3.3%
78 1
3.3%
79 1
3.3%
83 1
3.3%
86 1
3.3%
87 1
3.3%
ValueCountFrequency (%)
123 1
3.3%
122 1
3.3%
119 1
3.3%
118 1
3.3%
117 1
3.3%
114 1
3.3%
113 1
3.3%
112 1
3.3%
108 1
3.3%
104 1
3.3%

RNFL_T_8_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.933333
Minimum67
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:48.211507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile69.45
Q182.25
median93
Q3112.75
95-th percentile120.65
Maximum124
Range57
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation17.925003
Coefficient of variation (CV)0.18684854
Kurtosis-1.3055972
Mean95.933333
Median Absolute Deviation (MAD)16
Skewness-0.057954566
Sum2878
Variance321.30575
MonotonicityNot monotonic
2023-10-09T03:56:48.645052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
91 1
 
3.3%
118 1
 
3.3%
94 1
 
3.3%
113 1
 
3.3%
69 1
 
3.3%
105 1
 
3.3%
97 1
 
3.3%
122 1
 
3.3%
119 1
 
3.3%
71 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
67 1
3.3%
69 1
3.3%
70 1
3.3%
71 1
3.3%
73 1
3.3%
76 1
3.3%
78 1
3.3%
81 1
3.3%
86 1
3.3%
87 1
3.3%
ValueCountFrequency (%)
124 1
3.3%
122 1
3.3%
119 1
3.3%
118 1
3.3%
117 1
3.3%
116 1
3.3%
114 1
3.3%
113 1
3.3%
112 1
3.3%
108 1
3.3%

RNFL_T_9_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.866667
Minimum67
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:49.145867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile69.35
Q183.25
median97.5
Q3113.25
95-th percentile122.55
Maximum124
Range57
Interquartile range (IQR)30

Descriptive statistics

Standard deviation18.395527
Coefficient of variation (CV)0.18990564
Kurtosis-1.3308531
Mean96.866667
Median Absolute Deviation (MAD)15
Skewness-0.047377241
Sum2906
Variance338.3954
MonotonicityNot monotonic
2023-10-09T03:56:49.464817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
102 1
 
3.3%
108 1
 
3.3%
109 1
 
3.3%
82 1
 
3.3%
73 1
 
3.3%
85 1
 
3.3%
67 1
 
3.3%
117 1
 
3.3%
100 1
 
3.3%
111 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
67 1
3.3%
68 1
3.3%
71 1
3.3%
72 1
3.3%
73 1
3.3%
79 1
3.3%
82 1
3.3%
83 1
3.3%
84 1
3.3%
85 1
3.3%
ValueCountFrequency (%)
124 1
3.3%
123 1
3.3%
122 1
3.3%
121 1
3.3%
120 1
3.3%
117 1
3.3%
116 1
3.3%
114 1
3.3%
111 1
3.3%
109 1
3.3%

RNFL_T_9_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.433333
Minimum65
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:49.924660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.45
Q180.25
median98.5
Q3109.75
95-th percentile119.1
Maximum122
Range57
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.982143
Coefficient of variation (CV)0.19042157
Kurtosis-1.3181017
Mean94.433333
Median Absolute Deviation (MAD)15
Skewness-0.15603937
Sum2833
Variance323.35747
MonotonicityNot monotonic
2023-10-09T03:56:50.333358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
66 1
 
3.3%
67 1
 
3.3%
118 1
 
3.3%
104 1
 
3.3%
65 1
 
3.3%
80 1
 
3.3%
111 1
 
3.3%
81 1
 
3.3%
76 1
 
3.3%
99 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
67 1
3.3%
68 1
3.3%
74 1
3.3%
76 1
3.3%
78 1
3.3%
80 1
3.3%
81 1
3.3%
83 1
3.3%
ValueCountFrequency (%)
122 1
3.3%
120 1
3.3%
118 1
3.3%
116 1
3.3%
114 1
3.3%
113 1
3.3%
111 1
3.3%
110 1
3.3%
109 1
3.3%
108 1
3.3%

RNFL_T_10_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.633333
Minimum65
Maximum123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:50.693386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.45
Q178
median99.5
Q3109.75
95-th percentile119.2
Maximum123
Range58
Interquartile range (IQR)31.75

Descriptive statistics

Standard deviation18.609385
Coefficient of variation (CV)0.19664725
Kurtosis-1.3129848
Mean94.633333
Median Absolute Deviation (MAD)15
Skewness-0.2908051
Sum2839
Variance346.3092
MonotonicityNot monotonic
2023-10-09T03:56:51.125167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
100 1
 
3.3%
74 1
 
3.3%
103 1
 
3.3%
115 1
 
3.3%
66 1
 
3.3%
113 1
 
3.3%
117 1
 
3.3%
98 1
 
3.3%
105 1
 
3.3%
106 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
65 1
3.3%
66 1
3.3%
67 1
3.3%
68 1
3.3%
69 1
3.3%
70 1
3.3%
74 1
3.3%
77 1
3.3%
81 1
3.3%
82 1
3.3%
ValueCountFrequency (%)
123 1
3.3%
121 1
3.3%
117 1
3.3%
115 1
3.3%
114 1
3.3%
113 1
3.3%
112 1
3.3%
110 1
3.3%
109 1
3.3%
106 1
3.3%

RNFL_T_10_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.733333
Minimum66
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:51.493024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile68.9
Q179.25
median101.5
Q3112.25
95-th percentile122.1
Maximum125
Range59
Interquartile range (IQR)33

Descriptive statistics

Standard deviation18.586115
Coefficient of variation (CV)0.19213765
Kurtosis-1.3753986
Mean96.733333
Median Absolute Deviation (MAD)16
Skewness-0.20496644
Sum2902
Variance345.44368
MonotonicityNot monotonic
2023-10-09T03:56:51.742421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
110 1
 
3.3%
68 1
 
3.3%
105 1
 
3.3%
91 1
 
3.3%
113 1
 
3.3%
97 1
 
3.3%
81 1
 
3.3%
114 1
 
3.3%
76 1
 
3.3%
108 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
66 1
3.3%
68 1
3.3%
70 1
3.3%
72 1
3.3%
74 1
3.3%
76 1
3.3%
77 1
3.3%
79 1
3.3%
80 1
3.3%
81 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
123 1
3.3%
121 1
3.3%
118 1
3.3%
117 1
3.3%
115 1
3.3%
114 1
3.3%
113 1
3.3%
110 1
3.3%
109 1
3.3%

RNFL_T_11_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.866667
Minimum67
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:51.970110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile69.9
Q179.25
median99.5
Q3111.25
95-th percentile122.55
Maximum125
Range58
Interquartile range (IQR)32

Descriptive statistics

Standard deviation18.205216
Coefficient of variation (CV)0.18794098
Kurtosis-1.3239097
Mean96.866667
Median Absolute Deviation (MAD)17.5
Skewness-0.09397469
Sum2906
Variance331.42989
MonotonicityNot monotonic
2023-10-09T03:56:52.168201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
108 1
 
3.3%
112 1
 
3.3%
91 1
 
3.3%
101 1
 
3.3%
67 1
 
3.3%
115 1
 
3.3%
120 1
 
3.3%
123 1
 
3.3%
81 1
 
3.3%
119 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
67 1
3.3%
69 1
3.3%
71 1
3.3%
74 1
3.3%
76 1
3.3%
77 1
3.3%
78 1
3.3%
79 1
3.3%
80 1
3.3%
81 1
3.3%
ValueCountFrequency (%)
125 1
3.3%
123 1
3.3%
122 1
3.3%
120 1
3.3%
119 1
3.3%
116 1
3.3%
115 1
3.3%
112 1
3.3%
109 1
3.3%
108 1
3.3%

RNFL_T_11_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.5
Minimum66
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:52.563770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile67.45
Q176.25
median86.5
Q3103.5
95-th percentile113.55
Maximum117
Range51
Interquartile range (IQR)27.25

Descriptive statistics

Standard deviation15.8457
Coefficient of variation (CV)0.17704693
Kurtosis-1.3060662
Mean89.5
Median Absolute Deviation (MAD)13.5
Skewness0.16372232
Sum2685
Variance251.08621
MonotonicityNot monotonic
2023-10-09T03:56:52.795979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
81 1
 
3.3%
114 1
 
3.3%
107 1
 
3.3%
76 1
 
3.3%
94 1
 
3.3%
102 1
 
3.3%
88 1
 
3.3%
96 1
 
3.3%
67 1
 
3.3%
83 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
66 1
3.3%
67 1
3.3%
68 1
3.3%
70 1
3.3%
72 1
3.3%
73 1
3.3%
74 1
3.3%
76 1
3.3%
77 1
3.3%
78 1
3.3%
ValueCountFrequency (%)
117 1
3.3%
114 1
3.3%
113 1
3.3%
110 1
3.3%
108 1
3.3%
107 1
3.3%
106 1
3.3%
104 1
3.3%
102 1
3.3%
100 1
3.3%

AV_CD_R_R
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

AV_CD_R_L
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

VE_CD_R_R
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

VE_CD_R_L
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

CMT_ETDRS_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean311.8
Minimum245
Maximum380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:53.001173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum245
5-th percentile249.15
Q1282.5
median311.5
Q3345.25
95-th percentile373.5
Maximum380
Range135
Interquartile range (IQR)62.75

Descriptive statistics

Standard deviation40.953632
Coefficient of variation (CV)0.13134584
Kurtosis-1.1804812
Mean311.8
Median Absolute Deviation (MAD)33
Skewness-0.11337527
Sum9354
Variance1677.2
MonotonicityNot monotonic
2023-10-09T03:56:53.640339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
253 1
 
3.3%
284 1
 
3.3%
316 1
 
3.3%
332 1
 
3.3%
351 1
 
3.3%
339 1
 
3.3%
307 1
 
3.3%
340 1
 
3.3%
343 1
 
3.3%
245 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
245 1
3.3%
246 1
3.3%
253 1
3.3%
257 1
3.3%
258 1
3.3%
260 1
3.3%
277 1
3.3%
282 1
3.3%
284 1
3.3%
286 1
3.3%
ValueCountFrequency (%)
380 1
3.3%
378 1
3.3%
368 1
3.3%
354 1
3.3%
351 1
3.3%
349 1
3.3%
348 1
3.3%
346 1
3.3%
343 1
3.3%
340 1
3.3%

CMT_ETDRS_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean302.33333
Minimum247
Maximum380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:53.885368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum247
5-th percentile259.9
Q1276.25
median290.5
Q3323.75
95-th percentile366.25
Maximum380
Range133
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation35.933208
Coefficient of variation (CV)0.11885295
Kurtosis-0.60141008
Mean302.33333
Median Absolute Deviation (MAD)26.5
Skewness0.60538006
Sum9070
Variance1291.1954
MonotonicityNot monotonic
2023-10-09T03:56:54.176452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
283 1
 
3.3%
247 1
 
3.3%
298 1
 
3.3%
300 1
 
3.3%
282 1
 
3.3%
279 1
 
3.3%
320 1
 
3.3%
277 1
 
3.3%
319 1
 
3.3%
265 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
247 1
3.3%
259 1
3.3%
261 1
3.3%
265 1
3.3%
267 1
3.3%
269 1
3.3%
274 1
3.3%
276 1
3.3%
277 1
3.3%
279 1
3.3%
ValueCountFrequency (%)
380 1
3.3%
373 1
3.3%
358 1
3.3%
351 1
3.3%
346 1
3.3%
345 1
3.3%
327 1
3.3%
324 1
3.3%
323 1
3.3%
320 1
3.3%

SMT_3_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307.1
Minimum249
Maximum377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:54.486192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249
5-th percentile251.45
Q1283
median305.5
Q3332.5
95-th percentile362.55
Maximum377
Range128
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation36.232344
Coefficient of variation (CV)0.11798223
Kurtosis-0.91274941
Mean307.1
Median Absolute Deviation (MAD)26.5
Skewness0.040755386
Sum9213
Variance1312.7828
MonotonicityNot monotonic
2023-10-09T03:56:54.770272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
249 1
 
3.3%
291 1
 
3.3%
377 1
 
3.3%
325 1
 
3.3%
313 1
 
3.3%
314 1
 
3.3%
257 1
 
3.3%
260 1
 
3.3%
296 1
 
3.3%
363 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
249 1
3.3%
251 1
3.3%
252 1
3.3%
257 1
3.3%
260 1
3.3%
267 1
3.3%
278 1
3.3%
282 1
3.3%
286 1
3.3%
290 1
3.3%
ValueCountFrequency (%)
377 1
3.3%
363 1
3.3%
362 1
3.3%
353 1
3.3%
348 1
3.3%
336 1
3.3%
335 1
3.3%
333 1
3.3%
331 1
3.3%
330 1
3.3%

SMT_3_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean312.43333
Minimum245
Maximum372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:55.250675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum245
5-th percentile249.45
Q1273.5
median313.5
Q3350.5
95-th percentile370.55
Maximum372
Range127
Interquartile range (IQR)77

Descriptive statistics

Standard deviation42.064551
Coefficient of variation (CV)0.13463528
Kurtosis-1.48171
Mean312.43333
Median Absolute Deviation (MAD)39
Skewness-0.12541641
Sum9373
Variance1769.4264
MonotonicityNot monotonic
2023-10-09T03:56:55.721946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
354 1
 
3.3%
340 1
 
3.3%
298 1
 
3.3%
245 1
 
3.3%
339 1
 
3.3%
272 1
 
3.3%
372 1
 
3.3%
286 1
 
3.3%
351 1
 
3.3%
269 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
245 1
3.3%
249 1
3.3%
250 1
3.3%
260 1
3.3%
263 1
3.3%
267 1
3.3%
269 1
3.3%
272 1
3.3%
278 1
3.3%
284 1
3.3%
ValueCountFrequency (%)
372 1
3.3%
371 1
3.3%
370 1
3.3%
362 1
3.3%
357 1
3.3%
355 1
3.3%
354 1
3.3%
351 1
3.3%
349 1
3.3%
341 1
3.3%

IMT_3_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean300.13333
Minimum246
Maximum376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:55.999863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum246
5-th percentile247.45
Q1262.75
median284.5
Q3341.25
95-th percentile366.95
Maximum376
Range130
Interquartile range (IQR)78.5

Descriptive statistics

Standard deviation43.153881
Coefficient of variation (CV)0.14378237
Kurtosis-1.4227489
Mean300.13333
Median Absolute Deviation (MAD)29
Skewness0.40034361
Sum9004
Variance1862.2575
MonotonicityNot monotonic
2023-10-09T03:56:56.355670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
339 1
 
3.3%
271 1
 
3.3%
265 1
 
3.3%
288 1
 
3.3%
299 1
 
3.3%
273 1
 
3.3%
371 1
 
3.3%
306 1
 
3.3%
258 1
 
3.3%
248 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
246 1
3.3%
247 1
3.3%
248 1
3.3%
253 1
3.3%
258 1
3.3%
260 1
3.3%
261 1
3.3%
262 1
3.3%
265 1
3.3%
267 1
3.3%
ValueCountFrequency (%)
376 1
3.3%
371 1
3.3%
362 1
3.3%
357 1
3.3%
356 1
3.3%
350 1
3.3%
347 1
3.3%
342 1
3.3%
339 1
3.3%
338 1
3.3%

IMT_3_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean296.26667
Minimum249
Maximum378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:56.627708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249
5-th percentile254.45
Q1261.25
median285.5
Q3316.5
95-th percentile360.85
Maximum378
Range129
Interquartile range (IQR)55.25

Descriptive statistics

Standard deviation38.350411
Coefficient of variation (CV)0.12944558
Kurtosis-0.748099
Mean296.26667
Median Absolute Deviation (MAD)28
Skewness0.66636189
Sum8888
Variance1470.754
MonotonicityNot monotonic
2023-10-09T03:56:56.977077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
261 1
 
3.3%
332 1
 
3.3%
342 1
 
3.3%
280 1
 
3.3%
262 1
 
3.3%
295 1
 
3.3%
310 1
 
3.3%
279 1
 
3.3%
315 1
 
3.3%
255 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
249 1
3.3%
254 1
3.3%
255 1
3.3%
256 1
3.3%
257 1
3.3%
258 1
3.3%
259 1
3.3%
261 1
3.3%
262 1
3.3%
270 1
3.3%
ValueCountFrequency (%)
378 1
3.3%
364 1
3.3%
357 1
3.3%
355 1
3.3%
353 1
3.3%
342 1
3.3%
332 1
3.3%
317 1
3.3%
315 1
3.3%
314 1
3.3%

TMT_3_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean318.1
Minimum245
Maximum380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:57.323371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum245
5-th percentile252.35
Q1287.25
median313
Q3360.75
95-th percentile375.3
Maximum380
Range135
Interquartile range (IQR)73.5

Descriptive statistics

Standard deviation43.416468
Coefficient of variation (CV)0.13648685
Kurtosis-1.2875442
Mean318.1
Median Absolute Deviation (MAD)42
Skewness-0.1407733
Sum9543
Variance1884.9897
MonotonicityNot monotonic
2023-10-09T03:56:57.752186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
245 1
 
3.3%
294 1
 
3.3%
308 1
 
3.3%
260 1
 
3.3%
268 1
 
3.3%
254 1
 
3.3%
367 1
 
3.3%
305 1
 
3.3%
285 1
 
3.3%
306 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
245 1
3.3%
251 1
3.3%
254 1
3.3%
256 1
3.3%
260 1
3.3%
268 1
3.3%
279 1
3.3%
285 1
3.3%
294 1
3.3%
298 1
3.3%
ValueCountFrequency (%)
380 1
3.3%
378 1
3.3%
372 1
3.3%
370 1
3.3%
369 1
3.3%
367 1
3.3%
363 1
3.3%
361 1
3.3%
360 1
3.3%
352 1
3.3%

TMT_3_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310.23333
Minimum246
Maximum373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:57.996309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum246
5-th percentile250.9
Q1271.25
median306.5
Q3352.25
95-th percentile369.3
Maximum373
Range127
Interquartile range (IQR)81

Descriptive statistics

Standard deviation43.155439
Coefficient of variation (CV)0.13910639
Kurtosis-1.5304857
Mean310.23333
Median Absolute Deviation (MAD)43.5
Skewness-0.016509952
Sum9307
Variance1862.392
MonotonicityNot monotonic
2023-10-09T03:56:58.227384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
353 1
 
3.3%
250 1
 
3.3%
358 1
 
3.3%
340 1
 
3.3%
373 1
 
3.3%
246 1
 
3.3%
339 1
 
3.3%
366 1
 
3.3%
258 1
 
3.3%
356 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
246 1
3.3%
250 1
3.3%
252 1
3.3%
254 1
3.3%
258 1
3.3%
260 1
3.3%
263 1
3.3%
271 1
3.3%
272 1
3.3%
284 1
3.3%
ValueCountFrequency (%)
373 1
3.3%
372 1
3.3%
366 1
3.3%
362 1
3.3%
360 1
3.3%
358 1
3.3%
356 1
3.3%
353 1
3.3%
350 1
3.3%
346 1
3.3%

NMT_3_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean316
Minimum249
Maximum378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:58.461095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249
5-th percentile250.45
Q1276.5
median319
Q3358.25
95-th percentile375.65
Maximum378
Range129
Interquartile range (IQR)81.75

Descriptive statistics

Standard deviation44.466958
Coefficient of variation (CV)0.14071822
Kurtosis-1.5191992
Mean316
Median Absolute Deviation (MAD)42.5
Skewness-0.086955571
Sum9480
Variance1977.3103
MonotonicityNot monotonic
2023-10-09T03:56:58.709905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
260 1
 
3.3%
289 1
 
3.3%
249 1
 
3.3%
347 1
 
3.3%
284 1
 
3.3%
261 1
 
3.3%
366 1
 
3.3%
336 1
 
3.3%
251 1
 
3.3%
302 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
249 1
3.3%
250 1
3.3%
251 1
3.3%
260 1
3.3%
261 1
3.3%
266 1
3.3%
271 1
3.3%
276 1
3.3%
278 1
3.3%
284 1
3.3%
ValueCountFrequency (%)
378 1
3.3%
377 1
3.3%
374 1
3.3%
371 1
3.3%
367 1
3.3%
366 1
3.3%
362 1
3.3%
361 1
3.3%
350 1
3.3%
349 1
3.3%

NMT_3_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean315.36667
Minimum249
Maximum371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:58.986382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249
5-th percentile253.25
Q1284.75
median318
Q3350.5
95-th percentile366.55
Maximum371
Range122
Interquartile range (IQR)65.75

Descriptive statistics

Standard deviation37.840394
Coefficient of variation (CV)0.11998857
Kurtosis-1.0982741
Mean315.36667
Median Absolute Deviation (MAD)34
Skewness-0.20267064
Sum9461
Variance1431.8954
MonotonicityNot monotonic
2023-10-09T03:56:59.188942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
314 1
 
3.3%
322 1
 
3.3%
273 1
 
3.3%
367 1
 
3.3%
319 1
 
3.3%
351 1
 
3.3%
357 1
 
3.3%
263 1
 
3.3%
360 1
 
3.3%
304 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
249 1
3.3%
251 1
3.3%
256 1
3.3%
263 1
3.3%
273 1
3.3%
275 1
3.3%
276 1
3.3%
283 1
3.3%
290 1
3.3%
292 1
3.3%
ValueCountFrequency (%)
371 1
3.3%
367 1
3.3%
366 1
3.3%
362 1
3.3%
360 1
3.3%
358 1
3.3%
357 1
3.3%
351 1
3.3%
349 1
3.3%
341 1
3.3%

SMT_6_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310.3
Minimum246
Maximum379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:56:59.426857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum246
5-th percentile251.8
Q1276
median313
Q3347.75
95-th percentile369.1
Maximum379
Range133
Interquartile range (IQR)71.75

Descriptive statistics

Standard deviation42.562854
Coefficient of variation (CV)0.13716679
Kurtosis-1.478754
Mean310.3
Median Absolute Deviation (MAD)36.5
Skewness0.00060062619
Sum9309
Variance1811.5966
MonotonicityNot monotonic
2023-10-09T03:56:59.719104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
250 1
 
3.3%
355 1
 
3.3%
342 1
 
3.3%
347 1
 
3.3%
324 1
 
3.3%
279 1
 
3.3%
256 1
 
3.3%
328 1
 
3.3%
275 1
 
3.3%
323 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
246 1
3.3%
250 1
3.3%
254 1
3.3%
256 1
3.3%
258 1
3.3%
262 1
3.3%
264 1
3.3%
275 1
3.3%
279 1
3.3%
280 1
3.3%
ValueCountFrequency (%)
379 1
3.3%
370 1
3.3%
368 1
3.3%
363 1
3.3%
357 1
3.3%
356 1
3.3%
355 1
3.3%
348 1
3.3%
347 1
3.3%
342 1
3.3%

SMT_6_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307.83333
Minimum246
Maximum377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:57:00.137928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum246
5-th percentile247.45
Q1281
median310
Q3334.25
95-th percentile370.05
Maximum377
Range131
Interquartile range (IQR)53.25

Descriptive statistics

Standard deviation38.327161
Coefficient of variation (CV)0.12450621
Kurtosis-0.83125015
Mean307.83333
Median Absolute Deviation (MAD)26
Skewness-0.067350344
Sum9235
Variance1468.9713
MonotonicityNot monotonic
2023-10-09T03:57:01.049641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
335 1
 
3.3%
301 1
 
3.3%
316 1
 
3.3%
270 1
 
3.3%
258 1
 
3.3%
294 1
 
3.3%
306 1
 
3.3%
290 1
 
3.3%
292 1
 
3.3%
246 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
246 1
3.3%
247 1
3.3%
248 1
3.3%
251 1
3.3%
258 1
3.3%
262 1
3.3%
270 1
3.3%
278 1
3.3%
290 1
3.3%
292 1
3.3%
ValueCountFrequency (%)
377 1
3.3%
375 1
3.3%
364 1
3.3%
352 1
3.3%
344 1
3.3%
343 1
3.3%
337 1
3.3%
335 1
3.3%
332 1
3.3%
329 1
3.3%

IMT_6_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317.9
Minimum253
Maximum379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:57:01.537653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum253
5-th percentile263.45
Q1287.75
median314
Q3340.25
95-th percentile377.55
Maximum379
Range126
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation37.496069
Coefficient of variation (CV)0.11794926
Kurtosis-0.99903238
Mean317.9
Median Absolute Deviation (MAD)27
Skewness0.12547164
Sum9537
Variance1405.9552
MonotonicityNot monotonic
2023-10-09T03:57:01.782375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
264 1
 
3.3%
341 1
 
3.3%
287 1
 
3.3%
298 1
 
3.3%
263 1
 
3.3%
375 1
 
3.3%
356 1
 
3.3%
309 1
 
3.3%
253 1
 
3.3%
310 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
253 1
3.3%
263 1
3.3%
264 1
3.3%
268 1
3.3%
279 1
3.3%
283 1
3.3%
286 1
3.3%
287 1
3.3%
290 1
3.3%
298 1
3.3%
ValueCountFrequency (%)
379 1
3.3%
378 1
3.3%
377 1
3.3%
375 1
3.3%
367 1
3.3%
357 1
3.3%
356 1
3.3%
341 1
3.3%
338 1
3.3%
337 1
3.3%

IMT_6_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean311.46667
Minimum252
Maximum375
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:57:02.294926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum252
5-th percentile257.25
Q1279.5
median316.5
Q3343.25
95-th percentile364.15
Maximum375
Range123
Interquartile range (IQR)63.75

Descriptive statistics

Standard deviation37.107238
Coefficient of variation (CV)0.11913711
Kurtosis-1.3493126
Mean311.46667
Median Absolute Deviation (MAD)34
Skewness-0.020219699
Sum9344
Variance1376.9471
MonotonicityNot monotonic
2023-10-09T03:57:02.756092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
276 1
 
3.3%
327 1
 
3.3%
289 1
 
3.3%
252 1
 
3.3%
375 1
 
3.3%
318 1
 
3.3%
274 1
 
3.3%
260 1
 
3.3%
281 1
 
3.3%
266 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
252 1
3.3%
255 1
3.3%
260 1
3.3%
266 1
3.3%
269 1
3.3%
274 1
3.3%
276 1
3.3%
279 1
3.3%
281 1
3.3%
282 1
3.3%
ValueCountFrequency (%)
375 1
3.3%
370 1
3.3%
357 1
3.3%
354 1
3.3%
353 1
3.3%
346 1
3.3%
345 1
3.3%
344 1
3.3%
341 1
3.3%
339 1
3.3%

TMT_6_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean308.23333
Minimum248
Maximum375
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:57:02.999655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum248
5-th percentile252.45
Q1275.75
median310
Q3341
95-th percentile365.1
Maximum375
Range127
Interquartile range (IQR)65.25

Descriptive statistics

Standard deviation37.910678
Coefficient of variation (CV)0.12299344
Kurtosis-1.1640414
Mean308.23333
Median Absolute Deviation (MAD)33.5
Skewness0.05521537
Sum9247
Variance1437.2195
MonotonicityNot monotonic
2023-10-09T03:57:03.372617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
322 1
 
3.3%
333 1
 
3.3%
278 1
 
3.3%
282 1
 
3.3%
375 1
 
3.3%
291 1
 
3.3%
275 1
 
3.3%
271 1
 
3.3%
317 1
 
3.3%
324 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
248 1
3.3%
252 1
3.3%
253 1
3.3%
254 1
3.3%
271 1
3.3%
272 1
3.3%
274 1
3.3%
275 1
3.3%
278 1
3.3%
281 1
3.3%
ValueCountFrequency (%)
375 1
3.3%
366 1
3.3%
364 1
3.3%
359 1
3.3%
349 1
3.3%
346 1
3.3%
345 1
3.3%
342 1
3.3%
338 1
3.3%
333 1
3.3%

TMT_6_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean305.5
Minimum246
Maximum378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:57:03.675333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum246
5-th percentile248.8
Q1264.5
median301.5
Q3348.25
95-th percentile376.1
Maximum378
Range132
Interquartile range (IQR)83.75

Descriptive statistics

Standard deviation45.557656
Coefficient of variation (CV)0.1491249
Kurtosis-1.3640469
Mean305.5
Median Absolute Deviation (MAD)39
Skewness0.30586613
Sum9165
Variance2075.5
MonotonicityNot monotonic
2023-10-09T03:57:04.049091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
267 1
 
3.3%
334 1
 
3.3%
254 1
 
3.3%
357 1
 
3.3%
262 1
 
3.3%
251 1
 
3.3%
264 1
 
3.3%
266 1
 
3.3%
289 1
 
3.3%
367 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
246 1
3.3%
247 1
3.3%
251 1
3.3%
253 1
3.3%
254 1
3.3%
255 1
3.3%
262 1
3.3%
264 1
3.3%
266 1
3.3%
267 1
3.3%
ValueCountFrequency (%)
378 1
3.3%
377 1
3.3%
375 1
3.3%
373 1
3.3%
367 1
3.3%
359 1
3.3%
357 1
3.3%
351 1
3.3%
340 1
3.3%
334 1
3.3%

NMT_6_R
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307.9
Minimum245
Maximum380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:57:04.632452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum245
5-th percentile254.9
Q1274.25
median307
Q3336
95-th percentile374.1
Maximum380
Range135
Interquartile range (IQR)61.75

Descriptive statistics

Standard deviation39.593059
Coefficient of variation (CV)0.12859064
Kurtosis-0.99825025
Mean307.9
Median Absolute Deviation (MAD)31
Skewness0.24843327
Sum9237
Variance1567.6103
MonotonicityNot monotonic
2023-10-09T03:57:05.672710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
319 1
 
3.3%
288 1
 
3.3%
333 1
 
3.3%
245 1
 
3.3%
268 1
 
3.3%
364 1
 
3.3%
302 1
 
3.3%
294 1
 
3.3%
316 1
 
3.3%
260 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
245 1
3.3%
254 1
3.3%
256 1
3.3%
260 1
3.3%
261 1
3.3%
268 1
3.3%
269 1
3.3%
272 1
3.3%
281 1
3.3%
283 1
3.3%
ValueCountFrequency (%)
380 1
3.3%
375 1
3.3%
373 1
3.3%
364 1
3.3%
360 1
3.3%
342 1
3.3%
339 1
3.3%
337 1
3.3%
333 1
3.3%
331 1
3.3%

NMT_6_L
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean313.23333
Minimum252
Maximum380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-10-09T03:57:06.468765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum252
5-th percentile255.35
Q1278
median317
Q3345.25
95-th percentile372.05
Maximum380
Range128
Interquartile range (IQR)67.25

Descriptive statistics

Standard deviation39.319806
Coefficient of variation (CV)0.1255288
Kurtosis-1.2602009
Mean313.23333
Median Absolute Deviation (MAD)33.5
Skewness0.034938744
Sum9397
Variance1546.0471
MonotonicityNot monotonic
2023-10-09T03:57:06.888543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
297 1
 
3.3%
289 1
 
3.3%
270 1
 
3.3%
295 1
 
3.3%
330 1
 
3.3%
335 1
 
3.3%
269 1
 
3.3%
380 1
 
3.3%
326 1
 
3.3%
332 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
252 1
3.3%
254 1
3.3%
257 1
3.3%
266 1
3.3%
269 1
3.3%
270 1
3.3%
272 1
3.3%
277 1
3.3%
281 1
3.3%
289 1
3.3%
ValueCountFrequency (%)
380 1
3.3%
377 1
3.3%
366 1
3.3%
364 1
3.3%
360 1
3.3%
351 1
3.3%
350 1
3.3%
346 1
3.3%
343 1
3.3%
335 1
3.3%

Sample

PatIDsexage_octRNFL_T_12_RRNFL_T_12_LRNFL_T_1_RRNFL_T_1_LRNFL_T_2_RRNFL_T_2_LRNFL_T_3_RRNFL_T_3_LRNFL_T_4_RRNFL_T_4_LRNFL_T_5_RRNFL_T_5_LRNFL_T_6_RRNFL_T_6_LRNFL_T_7_RRNFL_T_7_LRNFL_T_8_RRNFL_T_8_LRNFL_T_9_RRNFL_T_9_LRNFL_T_10_RRNFL_T_10_LRNFL_T_11_RRNFL_T_11_LAV_CD_R_RAV_CD_R_LVE_CD_R_RVE_CD_R_LCMT_ETDRS_RCMT_ETDRS_LSMT_3_RSMT_3_LIMT_3_RIMT_3_LTMT_3_RTMT_3_LNMT_3_RNMT_3_LSMT_6_RSMT_6_LIMT_6_RIMT_6_LTMT_6_RTMT_6_LNMT_6_RNMT_6_L
01M4875101106709177991221251241118793114121123103911026610011010881<NA><NA><NA><NA>253283249354339261245353260314250335264276322267319297
12M3879121849012211588121121100929467658799119108837877106122110<NA><NA><NA><NA>306358319303338378321252362251262325378282349307375292
23F2911688124987990111114901031221021121251161031048872114109807485<NA><NA><NA><NA>380380292357260288279272250371254343337269272351256360
34M669066668111310181966575881087296741121231148784997976108<NA><NA><NA><NA>354318330370281254251321304316370375299354346246290329
45M678573759310965687575981068687778381101104798384708998<NA><NA><NA><NA>346259328289262317310299377366282278379353314255292308
56M55110818887878710165936711393789711083877084981041047982<NA><NA><NA><NA>277324278362376364352263276362337337357344281378261327
67F44100856797698310991661051241229999921061181128674114109125100<NA><NA><NA><NA>282280335341342283372301278256258314268346253298312254
78F7776961009299797810197118110971218177948610768109671219372<NA><NA><NA><NA>378269362338246292378346337249348329290323338253269343
89F74967210972125811121051167499107104871049677811161009612510468<NA><NA><NA><NA>368292298310333357361362378341303364279341359377339364
910F68959311412471928690697910189105124115687190124113110729984<NA><NA><NA><NA>258274251249280259256254367358300319286315342328281252
PatIDsexage_octRNFL_T_12_RRNFL_T_12_LRNFL_T_1_RRNFL_T_1_LRNFL_T_2_RRNFL_T_2_LRNFL_T_3_RRNFL_T_3_LRNFL_T_4_RRNFL_T_4_LRNFL_T_5_RRNFL_T_5_LRNFL_T_6_RRNFL_T_6_LRNFL_T_7_RRNFL_T_7_LRNFL_T_8_RRNFL_T_8_LRNFL_T_9_RRNFL_T_9_LRNFL_T_10_RRNFL_T_10_LRNFL_T_11_RRNFL_T_11_LAV_CD_R_RAV_CD_R_LVE_CD_R_RVE_CD_R_LCMT_ETDRS_RCMT_ETDRS_LSMT_3_RSMT_3_LIMT_3_RIMT_3_LTMT_3_RTMT_3_LNMT_3_RNMT_3_LSMT_6_RSMT_6_LIMT_6_RIMT_6_LTMT_6_RTMT_6_LNMT_6_RNMT_6_L
2021F837786741018610069125114102108691131119910910873123122821186973<NA><NA><NA><NA>246346331334253270351291331327357377335336306375331266
2122M498475938410591124120779510911266809797969295120102667174<NA><NA><NA><NA>289323290317267256345372350349330262327345301310337366
2223F621019812094108991136767688310010867816565711119910610811983<NA><NA><NA><NA>245265363269248255306356302304323246310266324367260332
2324F667210410269121103948771831151188074986711411910076105768167<NA><NA><NA><NA>343319296351258315285258251360275292253281317289316326
2425F711211108771821161221158711475104961021198779122117819811412396<NA><NA><NA><NA>340277260286306279305366336263328290309260271266294380
2526M5112280721077810876681068491956988105926697671111178112088<NA><NA><NA><NA>307320257372371310367339366357256306356274275264302269
2627M51103112821201046611998109781007591104969194105858011397115102<NA><NA><NA><NA>339279314272273295254246261351279294375318291251364335
2728F5411511196687511285721017780105117798411988697365661136794<NA><NA><NA><NA>351282313339299262268373284319324258263375375262268330
2829M606682108104651217366948665781151081118597113821041159110176<NA><NA><NA><NA>332300325245288280260340347367347270298252282357245295
2930F7111184110113981029193108826998737372121789410911810310591107<NA><NA><NA><NA>316298377298265342308358249273342316287289278254333270