Overview

Dataset statistics

Number of variables29
Number of observations3424
Missing cells242
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory490.0 B

Variable types

Boolean1
Numeric12
Categorical16

Warnings

user_id has constant value "183" Constant
uid has constant value "1" Constant
totalcount has constant value "125" Constant
agebin has constant value "2" Constant
newuid has constant value "1" Constant
runlengthprev has 242 (7.1%) missing values Missing

Reproduction

Analysis started2021-02-25 23:47:35.405206
Analysis finished2021-02-25 23:47:36.161678
Duration0.76 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

correct
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.1 KiB
True
3271 
False
 
153
ValueCountFrequency (%)
True3271
95.5%
False153
 
4.5%

game_result_id
Real number (ℝ≥0)

Distinct49
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50029.30637
Minimum47986
Maximum51985
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:36.286515image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum47986
5-th percentile48256
Q149008
median49802
Q351069
95-th percentile51906
Maximum51985
Range3999
Interquartile range (IQR)2061

Descriptive statistics

Standard deviation1260.955837
Coefficient of variation (CV)0.02520434379
Kurtosis-1.41843207
Mean50029.30637
Median Absolute Deviation (MAD)1036
Skewness0.09574972514
Sum171300345
Variance1590009.624
MonotocityNot monotonic
2021-02-26T00:47:36.424038image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
5190680
 
2.3%
5190380
 
2.3%
5190580
 
2.3%
5139579
 
2.3%
4907378
 
2.3%
4906878
 
2.3%
4907078
 
2.3%
5101078
 
2.3%
5198577
 
2.2%
4907677
 
2.2%
Other values (39)2639
77.1%
ValueCountFrequency (%)
4798640
1.2%
4798753
1.5%
4798947
1.4%
4825655
1.6%
4825765
1.9%
4825865
1.9%
4826064
1.9%
4890549
1.4%
4891559
1.7%
4891763
1.8%
ValueCountFrequency (%)
5198577
2.2%
5190776
2.2%
5190680
2.3%
5190580
2.3%
5190476
2.2%
5190380
2.3%
5139579
2.3%
5139472
2.1%
5137171
2.1%
5129974
2.2%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
R
897 
U
871 
D
840 
L
816 

Characters and Unicode

Total characters3424
Distinct characters4
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowR
2nd rowU
3rd rowD
4th rowD
5th rowR
ValueCountFrequency (%)
R897
26.2%
U871
25.4%
D840
24.5%
L816
23.8%
ValueCountFrequency (%)
r897
26.2%
u871
25.4%
d840
24.5%
l816
23.8%

Most occurring characters

ValueCountFrequency (%)
R897
26.2%
U871
25.4%
D840
24.5%
L816
23.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
R897
26.2%
U871
25.4%
D840
24.5%
L816
23.8%

Most occurring scripts

ValueCountFrequency (%)
Latin3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
R897
26.2%
U871
25.4%
D840
24.5%
L816
23.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
R897
26.2%
U871
25.4%
D840
24.5%
L816
23.8%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
R
872 
D
853 
U
851 
L
848 

Characters and Unicode

Total characters3424
Distinct characters4
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowR
2nd rowU
3rd rowD
4th rowD
5th rowR
ValueCountFrequency (%)
R872
25.5%
D853
24.9%
U851
24.9%
L848
24.8%
ValueCountFrequency (%)
r872
25.5%
d853
24.9%
u851
24.9%
l848
24.8%

Most occurring characters

ValueCountFrequency (%)
R872
25.5%
D853
24.9%
U851
24.9%
L848
24.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
R872
25.5%
D853
24.9%
U851
24.9%
L848
24.8%

Most occurring scripts

ValueCountFrequency (%)
Latin3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
R872
25.5%
D853
24.9%
U851
24.9%
L848
24.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
R872
25.5%
D853
24.9%
U851
24.9%
L848
24.8%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
R
880 
D
863 
L
851 
U
830 

Characters and Unicode

Total characters3424
Distinct characters4
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowR
2nd rowU
3rd rowD
4th rowD
5th rowR
ValueCountFrequency (%)
R880
25.7%
D863
25.2%
L851
24.9%
U830
24.2%
ValueCountFrequency (%)
r880
25.7%
d863
25.2%
l851
24.9%
u830
24.2%

Most occurring characters

ValueCountFrequency (%)
R880
25.7%
D863
25.2%
L851
24.9%
U830
24.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
R880
25.7%
D863
25.2%
L851
24.9%
U830
24.2%

Most occurring scripts

ValueCountFrequency (%)
Latin3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
R880
25.7%
D863
25.2%
L851
24.9%
U830
24.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
R880
25.7%
D863
25.2%
L851
24.9%
U830
24.2%

response_time
Real number (ℝ≥0)

Distinct703
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean800.3717874
Minimum212
Maximum2921
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:36.884116image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum212
5-th percentile621
Q1692
median752
Q3858
95-th percentile1125
Maximum2921
Range2709
Interquartile range (IQR)166

Descriptive statistics

Standard deviation187.9602643
Coefficient of variation (CV)0.2348411917
Kurtosis16.28080182
Mean800.3717874
Median Absolute Deviation (MAD)73
Skewness2.891247563
Sum2740473
Variance35329.06097
MonotocityNot monotonic
2021-02-26T00:47:37.013882image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71432
 
0.9%
72631
 
0.9%
72531
 
0.9%
69229
 
0.8%
70329
 
0.8%
70228
 
0.8%
68026
 
0.8%
68125
 
0.7%
73725
 
0.7%
73624
 
0.7%
Other values (693)3144
91.8%
ValueCountFrequency (%)
2121
< 0.1%
2181
< 0.1%
2531
< 0.1%
2851
< 0.1%
3261
< 0.1%
3401
< 0.1%
3441
< 0.1%
3791
< 0.1%
3841
< 0.1%
3871
< 0.1%
ValueCountFrequency (%)
29211
< 0.1%
24341
< 0.1%
24161
< 0.1%
22701
< 0.1%
21261
< 0.1%
21071
< 0.1%
20601
< 0.1%
20461
< 0.1%
20382
0.1%
19881
< 0.1%

trial_num
Real number (ℝ≥0)

Distinct84
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.80403037
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:37.150527image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q119
median37
Q356
95-th percentile74
Maximum84
Range83
Interquartile range (IQR)37

Descriptive statistics

Standard deviation22.05120793
Coefficient of variation (CV)0.5833030952
Kurtosis-1.113330421
Mean37.80403037
Median Absolute Deviation (MAD)19
Skewness0.0978722568
Sum129441
Variance486.2557711
MonotocityNot monotonic
2021-02-26T00:47:37.276279image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1249
 
1.4%
1449
 
1.4%
1649
 
1.4%
2449
 
1.4%
4248
 
1.4%
4448
 
1.4%
2548
 
1.4%
1548
 
1.4%
2948
 
1.4%
3348
 
1.4%
Other values (74)2940
85.9%
ValueCountFrequency (%)
142
1.2%
246
1.3%
347
1.4%
448
1.4%
548
1.4%
647
1.4%
746
1.3%
847
1.4%
945
1.3%
1048
1.4%
ValueCountFrequency (%)
842
 
0.1%
832
 
0.1%
827
 
0.2%
8111
 
0.3%
8012
0.4%
7913
0.4%
7818
0.5%
7723
0.7%
7629
0.8%
7529
0.8%

trial_type
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
P
1777 
M
1647 

Characters and Unicode

Total characters3424
Distinct characters2
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowP
2nd rowP
3rd rowP
4th rowP
5th rowP
ValueCountFrequency (%)
P1777
51.9%
M1647
48.1%
ValueCountFrequency (%)
p1777
51.9%
m1647
48.1%

Most occurring characters

ValueCountFrequency (%)
P1777
51.9%
M1647
48.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
P1777
51.9%
M1647
48.1%

Most occurring scripts

ValueCountFrequency (%)
Latin3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
P1777
51.9%
M1647
48.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
P1777
51.9%
M1647
48.1%

user_id
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.4 KiB
183
3424 

Characters and Unicode

Total characters10272
Distinct characters3
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

Unique0 ?
Unique (%)0.0%

Sample

1st row183
2nd row183
3rd row183
4th row183
5th row183
ValueCountFrequency (%)
1833424
100.0%
ValueCountFrequency (%)
1833424
100.0%

Most occurring characters

ValueCountFrequency (%)
13424
33.3%
83424
33.3%
33424
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number10272
100.0%

Most frequent character per category

ValueCountFrequency (%)
13424
33.3%
83424
33.3%
33424
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common10272
100.0%

Most frequent character per script

ValueCountFrequency (%)
13424
33.3%
83424
33.3%
33424
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII10272
100.0%

Most frequent character per block

ValueCountFrequency (%)
13424
33.3%
83424
33.3%
33424
33.3%

accuracy
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
1
3271 
0
 
153

Characters and Unicode

Total characters3424
Distinct characters2
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

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
13271
95.5%
0153
 
4.5%
ValueCountFrequency (%)
13271
95.5%
0153
 
4.5%

Most occurring characters

ValueCountFrequency (%)
13271
95.5%
0153
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
13271
95.5%
0153
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
13271
95.5%
0153
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
13271
95.5%
0153
 
4.5%

uid
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
1
3424 

Characters and Unicode

Total characters3424
Distinct characters1
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

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
13424
100.0%
ValueCountFrequency (%)
13424
100.0%

Most occurring characters

ValueCountFrequency (%)
13424
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
13424
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
13424
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
13424
100.0%

compatible
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
1
1740 
0
1684 

Characters and Unicode

Total characters3424
Distinct characters2
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

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
11740
50.8%
01684
49.2%
ValueCountFrequency (%)
11740
50.8%
01684
49.2%

Most occurring characters

ValueCountFrequency (%)
11740
50.8%
01684
49.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
11740
50.8%
01684
49.2%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
11740
50.8%
01684
49.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
11740
50.8%
01684
49.2%

gamecount
Real number (ℝ≥0)

Distinct49
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.18545561
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:37.910589image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q115
median29
Q343
95-th percentile55
Maximum60
Range59
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.32928073
Coefficient of variation (CV)0.5595006277
Kurtosis-1.092027542
Mean29.18545561
Median Absolute Deviation (MAD)14
Skewness0.0729068468
Sum99931
Variance266.6454092
MonotocityNot monotonic
2021-02-26T00:47:38.031912image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
5580
 
2.3%
5480
 
2.3%
5180
 
2.3%
4979
 
2.3%
4178
 
2.3%
2478
 
2.3%
2278
 
2.3%
1978
 
2.3%
4377
 
2.2%
6077
 
2.2%
Other values (39)2639
77.1%
ValueCountFrequency (%)
140
1.2%
253
1.5%
347
1.4%
455
1.6%
565
1.9%
665
1.9%
764
1.9%
849
1.4%
959
1.7%
1063
1.8%
ValueCountFrequency (%)
6077
2.2%
5676
2.2%
5580
2.3%
5480
2.3%
5276
2.2%
5180
2.3%
4979
2.3%
4772
2.1%
4671
2.1%
4574
2.2%

totalcount
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.4 KiB
125
3424 

Characters and Unicode

Total characters10272
Distinct characters3
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

Unique0 ?
Unique (%)0.0%

Sample

1st row125
2nd row125
3rd row125
4th row125
5th row125
ValueCountFrequency (%)
1253424
100.0%
ValueCountFrequency (%)
1253424
100.0%

Most occurring characters

ValueCountFrequency (%)
13424
33.3%
23424
33.3%
53424
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number10272
100.0%

Most frequent character per category

ValueCountFrequency (%)
13424
33.3%
23424
33.3%
53424
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common10272
100.0%

Most frequent character per script

ValueCountFrequency (%)
13424
33.3%
23424
33.3%
53424
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII10272
100.0%

Most frequent character per block

ValueCountFrequency (%)
13424
33.3%
23424
33.3%
53424
33.3%

agebin
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
2
3424 

Characters and Unicode

Total characters3424
Distinct characters1
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2
ValueCountFrequency (%)
23424
100.0%
ValueCountFrequency (%)
23424
100.0%

Most occurring characters

ValueCountFrequency (%)
23424
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
23424
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
23424
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
23424
100.0%

trialtypecount
Real number (ℝ≥0)

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.653621495
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:38.555639image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile8
Maximum13
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.33188439
Coefficient of variation (CV)0.6382391807
Kurtosis0.5117298265
Mean3.653621495
Median Absolute Deviation (MAD)2
Skewness0.9322119801
Sum12510
Variance5.437684807
MonotocityNot monotonic
2021-02-26T00:47:38.650201image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1684
20.0%
2635
18.5%
3571
16.7%
4472
13.8%
5360
10.5%
6262
 
7.7%
7185
 
5.4%
8122
 
3.6%
966
 
1.9%
1037
 
1.1%
Other values (3)30
 
0.9%
ValueCountFrequency (%)
1684
20.0%
2635
18.5%
3571
16.7%
4472
13.8%
5360
10.5%
6262
 
7.7%
7185
 
5.4%
8122
 
3.6%
966
 
1.9%
1037
 
1.1%
ValueCountFrequency (%)
135
 
0.1%
128
 
0.2%
1117
 
0.5%
1037
 
1.1%
966
 
1.9%
8122
 
3.6%
7185
 
5.4%
6262
7.7%
5360
10.5%
4472
13.8%

rtsum
Real number (ℝ≥0)

Distinct2478
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2942.023364
Minimum212
Maximum14052
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:38.757355image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum212
5-th percentile747
Q11472.75
median2501.5
Q34017.75
95-th percentile6589.25
Maximum14052
Range13840
Interquartile range (IQR)2545

Descriptive statistics

Standard deviation1925.73271
Coefficient of variation (CV)0.6545606446
Kurtosis1.708100294
Mean2942.023364
Median Absolute Deviation (MAD)1193
Skewness1.17350725
Sum10073488
Variance3708446.47
MonotocityNot monotonic
2021-02-26T00:47:38.877807image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8157
 
0.2%
8226
 
0.2%
8956
 
0.2%
7786
 
0.2%
14856
 
0.2%
7255
 
0.1%
7145
 
0.1%
9275
 
0.1%
8345
 
0.1%
7925
 
0.1%
Other values (2468)3368
98.4%
ValueCountFrequency (%)
2121
< 0.1%
2181
< 0.1%
2531
< 0.1%
2851
< 0.1%
3261
< 0.1%
3401
< 0.1%
3441
< 0.1%
3791
< 0.1%
3841
< 0.1%
3871
< 0.1%
ValueCountFrequency (%)
140521
< 0.1%
130511
< 0.1%
121641
< 0.1%
119921
< 0.1%
114291
< 0.1%
114111
< 0.1%
111931
< 0.1%
109691
< 0.1%
106581
< 0.1%
105741
< 0.1%

runlength
Real number (ℝ≥0)

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.277161215
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:38.982672image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q38
95-th percentile11
Maximum13
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.568374026
Coefficient of variation (CV)0.4091617115
Kurtosis-0.2973719233
Mean6.277161215
Median Absolute Deviation (MAD)2
Skewness0.3020572337
Sum21493
Variance6.596545138
MonotocityNot monotonic
2021-02-26T00:47:39.069148image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5527
15.4%
7492
14.4%
6426
12.4%
8420
12.3%
4405
11.8%
3300
8.8%
9266
7.8%
10200
 
5.8%
2148
 
4.3%
1193
 
2.7%
Other values (3)147
 
4.3%
ValueCountFrequency (%)
151
 
1.5%
2148
 
4.3%
3300
8.8%
4405
11.8%
5527
15.4%
6426
12.4%
7492
14.4%
8420
12.3%
9266
7.8%
10200
 
5.8%
ValueCountFrequency (%)
1362
 
1.8%
1234
 
1.0%
1193
 
2.7%
10200
 
5.8%
9266
7.8%
8420
12.3%
7492
14.4%
6426
12.4%
5527
15.4%
4405
11.8%

maxrtblock
Real number (ℝ≥0)

Distinct680
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5005.564836
Minimum682
Maximum14052
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:39.167700image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum682
5-th percentile1735.1
Q13414
median4833
Q36292.75
95-th percentile9050
Maximum14052
Range13370
Interquartile range (IQR)2878.75

Descriptive statistics

Standard deviation2205.264083
Coefficient of variation (CV)0.4405624849
Kurtosis0.838521816
Mean5005.564836
Median Absolute Deviation (MAD)1437
Skewness0.7053398591
Sum17139054
Variance4863189.674
MonotocityNot monotonic
2021-02-26T00:47:39.291279image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
723520
 
0.6%
452117
 
0.5%
673317
 
0.5%
607717
 
0.5%
565715
 
0.4%
798915
 
0.4%
691715
 
0.4%
509714
 
0.4%
486713
 
0.4%
482613
 
0.4%
Other values (670)3268
95.4%
ValueCountFrequency (%)
6821
< 0.1%
6841
< 0.1%
6851
< 0.1%
6951
< 0.1%
7031
< 0.1%
7121
< 0.1%
7131
< 0.1%
7152
0.1%
7251
< 0.1%
7311
< 0.1%
ValueCountFrequency (%)
1405212
0.4%
1216410
0.3%
1142912
0.4%
114118
0.2%
106589
0.3%
1055113
0.4%
1042612
0.4%
103349
0.3%
1031812
0.4%
98408
0.2%

runlengthprev
Real number (ℝ≥0)

MISSING

Distinct13
Distinct (%)0.4%
Missing242
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean5.05185418
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:39.392368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile10
Maximum13
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.517617526
Coefficient of variation (CV)0.4983551457
Kurtosis-0.07733253587
Mean5.05185418
Median Absolute Deviation (MAD)2
Skewness0.5286485988
Sum16075
Variance6.338398007
MonotocityNot monotonic
2021-02-26T00:47:39.478639image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5522
15.2%
4482
14.1%
3446
13.0%
7365
10.7%
2324
9.5%
6316
9.2%
8225
6.6%
1190
 
5.5%
9147
 
4.3%
1085
 
2.5%
Other values (3)80
 
2.3%
(Missing)242
7.1%
ValueCountFrequency (%)
1190
 
5.5%
2324
9.5%
3446
13.0%
4482
14.1%
5522
15.2%
6316
9.2%
7365
10.7%
8225
6.6%
9147
 
4.3%
1085
 
2.5%
ValueCountFrequency (%)
1325
 
0.7%
127
 
0.2%
1148
 
1.4%
1085
 
2.5%
9147
 
4.3%
8225
6.6%
7365
10.7%
6316
9.2%
5522
15.2%
4482
14.1%

rtsumprev
Real number (ℝ≥0)

Distinct639
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3744.828855
Minimum20
Maximum14052
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:39.578384image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q12217.25
median3612
Q35096
95-th percentile7660.6
Maximum14052
Range14032
Interquartile range (IQR)2878.75

Descriptive statistics

Standard deviation2273.316357
Coefficient of variation (CV)0.6070548069
Kurtosis0.6372573805
Mean3744.828855
Median Absolute Deviation (MAD)1442
Skewness0.6225977513
Sum12822294
Variance5167967.261
MonotocityNot monotonic
2021-02-26T00:47:39.690330image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20242
 
7.1%
173316
 
0.5%
338015
 
0.4%
228314
 
0.4%
493414
 
0.4%
582313
 
0.4%
365713
 
0.4%
282613
 
0.4%
351113
 
0.4%
243712
 
0.4%
Other values (629)3059
89.3%
ValueCountFrequency (%)
20242
7.1%
6826
 
0.2%
6841
 
< 0.1%
6855
 
0.1%
6952
 
0.1%
7032
 
0.1%
7123
 
0.1%
7136
 
0.2%
7152
 
0.1%
7313
 
0.1%
ValueCountFrequency (%)
140523
 
0.1%
121643
 
0.1%
114296
0.2%
114119
0.3%
106586
0.2%
105513
 
0.1%
104266
0.2%
103342
 
0.1%
103186
0.2%
98402
 
0.1%

isswitch
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
0
2782 
1
642 

Characters and Unicode

Total characters3424
Distinct characters2
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

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
02782
81.2%
1642
 
18.8%
ValueCountFrequency (%)
02782
81.2%
1642
 
18.8%

Most occurring characters

ValueCountFrequency (%)
02782
81.2%
1642
 
18.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
02782
81.2%
1642
 
18.8%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
02782
81.2%
1642
 
18.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
02782
81.2%
1642
 
18.8%

movementd
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
2
897 
3
871 
4
840 
1
816 

Characters and Unicode

Total characters3424
Distinct characters4
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row4
4th row4
5th row2
ValueCountFrequency (%)
2897
26.2%
3871
25.4%
4840
24.5%
1816
23.8%
ValueCountFrequency (%)
2897
26.2%
3871
25.4%
4840
24.5%
1816
23.8%

Most occurring characters

ValueCountFrequency (%)
2897
26.2%
3871
25.4%
4840
24.5%
1816
23.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
2897
26.2%
3871
25.4%
4840
24.5%
1816
23.8%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
2897
26.2%
3871
25.4%
4840
24.5%
1816
23.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
2897
26.2%
3871
25.4%
4840
24.5%
1816
23.8%

pointingd
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
2
872 
4
853 
3
851 
1
848 

Characters and Unicode

Total characters3424
Distinct characters4
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row4
4th row4
5th row2
ValueCountFrequency (%)
2872
25.5%
4853
24.9%
3851
24.9%
1848
24.8%
ValueCountFrequency (%)
2872
25.5%
4853
24.9%
3851
24.9%
1848
24.8%

Most occurring characters

ValueCountFrequency (%)
2872
25.5%
4853
24.9%
3851
24.9%
1848
24.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
2872
25.5%
4853
24.9%
3851
24.9%
1848
24.8%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
2872
25.5%
4853
24.9%
3851
24.9%
1848
24.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
2872
25.5%
4853
24.9%
3851
24.9%
1848
24.8%

task
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
2
1777 
1
1647 

Characters and Unicode

Total characters3424
Distinct characters2
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2
ValueCountFrequency (%)
21777
51.9%
11647
48.1%
ValueCountFrequency (%)
21777
51.9%
11647
48.1%

Most occurring characters

ValueCountFrequency (%)
21777
51.9%
11647
48.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
21777
51.9%
11647
48.1%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
21777
51.9%
11647
48.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
21777
51.9%
11647
48.1%

choice
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
2
880 
4
863 
1
851 
3
830 

Characters and Unicode

Total characters3424
Distinct characters4
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row4
4th row4
5th row2
ValueCountFrequency (%)
2880
25.7%
4863
25.2%
1851
24.9%
3830
24.2%
ValueCountFrequency (%)
2880
25.7%
4863
25.2%
1851
24.9%
3830
24.2%

Most occurring characters

ValueCountFrequency (%)
2880
25.7%
4863
25.2%
1851
24.9%
3830
24.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
2880
25.7%
4863
25.2%
1851
24.9%
3830
24.2%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
2880
25.7%
4863
25.2%
1851
24.9%
3830
24.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
2880
25.7%
4863
25.2%
1851
24.9%
3830
24.2%

rlprev
Real number (ℝ≥0)

Distinct14
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.108352804
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:40.259368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile20
Maximum20
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.535535065
Coefficient of variation (CV)0.7425136057
Kurtosis3.505809002
Mean6.108352804
Median Absolute Deviation (MAD)2
Skewness1.904584971
Sum20915
Variance20.57107833
MonotocityNot monotonic
2021-02-26T00:47:40.343079image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
5522
15.2%
4482
14.1%
3446
13.0%
7365
10.7%
2324
9.5%
6316
9.2%
20242
7.1%
8225
6.6%
1190
 
5.5%
9147
 
4.3%
Other values (4)165
 
4.8%
ValueCountFrequency (%)
1190
 
5.5%
2324
9.5%
3446
13.0%
4482
14.1%
5522
15.2%
6316
9.2%
7365
10.7%
8225
6.6%
9147
 
4.3%
1085
 
2.5%
ValueCountFrequency (%)
20242
7.1%
1325
 
0.7%
127
 
0.2%
1148
 
1.4%
1085
 
2.5%
9147
 
4.3%
8225
6.6%
7365
10.7%
6316
9.2%
5522
15.2%

newuid
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size220.7 KiB
1
3424 

Characters and Unicode

Total characters3424
Distinct characters1
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

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
13424
100.0%
ValueCountFrequency (%)
13424
100.0%

Most occurring characters

ValueCountFrequency (%)
13424
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3424
100.0%

Most frequent character per category

ValueCountFrequency (%)
13424
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3424
100.0%

Most frequent character per script

ValueCountFrequency (%)
13424
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3424
100.0%

Most frequent character per block

ValueCountFrequency (%)
13424
100.0%

trialtypecount2
Real number (ℝ≥0)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.581191589
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size53.5 KiB
2021-02-26T00:47:40.517721image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.149769756
Coefficient of variation (CV)0.6002945395
Kurtosis-0.70981439
Mean3.581191589
Median Absolute Deviation (MAD)2
Skewness0.5819494996
Sum12262
Variance4.621510002
MonotocityNot monotonic
2021-02-26T00:47:40.597997image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1684
20.0%
2635
18.5%
3571
16.7%
4472
13.8%
5360
10.5%
6262
 
7.7%
8255
 
7.4%
7185
 
5.4%
ValueCountFrequency (%)
1684
20.0%
2635
18.5%
3571
16.7%
4472
13.8%
5360
10.5%
6262
 
7.7%
7185
 
5.4%
8255
 
7.4%
ValueCountFrequency (%)
8255
 
7.4%
7185
 
5.4%
6262
 
7.7%
5360
10.5%
4472
13.8%
3571
16.7%
2635
18.5%
1684
20.0%