heart_statlog

Dataset statistics

Number of variables	14
Number of observations	270
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	29.7 KiB
Average record size in memory	112.5 B

Variable types

CAT	5
NUM	5
BOOL	4

Reproduction

Analysis started	2020-08-25 01:24:36.260619
Analysis finished	2020-08-25 01:24:40.717365
Duration	4.46 seconds
Version	pandas-profiling v2.8.0
Command line	`pandas_profiling --config_file config.yaml [YOUR_FILE.csv]`
Download configuration	config.yaml

Warnings

oldpeak has 85 (31.5%) zeros Zeros

age
Real number (ℝ_≥0)

Distinct count	41
Unique (%)	15.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	54.43333333333333
Minimum	29.0
Maximum	77.0
Zeros	0
Zeros (%)	0.0%
Memory size	2.2 KiB

Quantile statistics

Minimum	29
5-th percentile	40
Q1	48
median	55
Q3	61
95-th percentile	68
Maximum	77
Range	48
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	9.109066524
Coefficient of variation (CV)	0.1673435369
Kurtosis	-0.544815393
Mean	54.43333333
Median Absolute Deviation (MAD)	7
Skewness	-0.1636152273
Sum	14697
Variance	82.97509294

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
54	16	5.9%
58	15	5.6%
51	12	4.4%
59	12	4.4%
60	12	4.4%
57	12	4.4%
52	11	4.1%
62	11	4.1%
44	10	3.7%
56	9	3.3%
64	9	3.3%
41	9	3.3%
65	8	3.0%
42	8	3.0%
67	8	3.0%
48	7	2.6%
43	7	2.6%
53	7	2.6%
61	7	2.6%
63	7	2.6%
50	7	2.6%
46	7	2.6%
45	7	2.6%
66	6	2.2%
55	6	2.2%
Other values (16)	40	14.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
29	1	0.4%
34	2	0.7%
35	3	1.1%
37	2	0.7%
38	1	0.4%
39	3	1.1%
40	3	1.1%
41	9	3.3%
42	8	3.0%
43	7	2.6%

Value	Count	Frequency (%)
77	1	0.4%
76	1	0.4%
74	1	0.4%
71	3	1.1%
70	4	1.5%
69	3	1.1%
68	3	1.1%
67	8	3.0%
66	6	2.2%
65	8	3.0%

sex
Boolean

Distinct count	2
Unique (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

1	183
0	87

Frequency Table

Value	Count	Frequency (%)
1	183	67.8%
0	87	32.2%

chest
Categorical

Distinct count	4
Unique (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

4	129
3	79
2	42
1	20

Value	Count	Frequency (%)
4	129	47.8%
3	79	29.3%
2	42	15.6%
1	20	7.4%

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Overview of Unicode Properties

Unique unicode characters	6
Unique unicode categories (?)	2
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
4	129	15.9%
3	79	9.8%
2	42	5.2%
1	20	2.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	540	66.7%
Other Punctuation	270	33.3%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
0	270	50.0%
4	129	23.9%
3	79	14.6%
2	42	7.8%
1	20	3.7%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
.	270	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	810	100.0%

Most frequent Common characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
4	129	15.9%
3	79	9.8%
2	42	5.2%
1	20	2.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	810	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
4	129	15.9%
3	79	9.8%
2	42	5.2%
1	20	2.5%

resting_blood_pressure
Real number (ℝ_≥0)

Distinct count	47
Unique (%)	17.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	131.34444444444443
Minimum	94.0
Maximum	200.0
Zeros	0
Zeros (%)	0.0%
Memory size	2.2 KiB

Quantile statistics

Minimum	94
5-th percentile	106.9
Q1	120
median	130
Q3	140
95-th percentile	160
Maximum	200
Range	106
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	17.86160829
Coefficient of variation (CV)	0.1359905885
Kurtosis	0.9230967359
Mean	131.3444444
Median Absolute Deviation (MAD)	10
Skewness	0.722618007
Sum	35463
Variance	319.0370508

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
120	34	12.6%
130	31	11.5%
140	30	11.1%
110	17	6.3%
150	17	6.3%
160	11	4.1%
125	10	3.7%
128	9	3.3%
112	9	3.3%
138	9	3.3%
118	7	2.6%
135	6	2.2%
108	6	2.2%
132	6	2.2%
124	5	1.9%
145	5	1.9%
100	4	1.5%
134	4	1.5%
152	4	1.5%
136	3	1.1%
142	3	1.1%
115	3	1.1%
122	3	1.1%
126	3	1.1%
105	3	1.1%
Other values (22)	28	10.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
94	2	0.7%
100	4	1.5%
101	1	0.4%
102	2	0.7%
104	1	0.4%
105	3	1.1%
106	1	0.4%
108	6	2.2%
110	17	6.3%
112	9	3.3%

Value	Count	Frequency (%)
200	1	0.4%
192	1	0.4%
180	3	1.1%
178	2	0.7%
174	1	0.4%
172	1	0.4%
170	2	0.7%
165	1	0.4%
160	11	4.1%
158	1	0.4%

serum_cholestoral
Real number (ℝ_≥0)

Distinct count	144
Unique (%)	53.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	249.65925925925927
Minimum	126.0
Maximum	564.0
Zeros	0
Zeros (%)	0.0%
Memory size	2.2 KiB

Quantile statistics

Minimum	126
5-th percentile	177
Q1	213
median	245
Q3	280
95-th percentile	326.55
Maximum	564
Range	438
Interquartile range (IQR)	67

Descriptive statistics

Standard deviation	51.68623712
Coefficient of variation (CV)	0.2070271188
Kurtosis	4.89559899
Mean	249.6592593
Median Absolute Deviation (MAD)	32.5
Skewness	1.183720889
Sum	67408
Variance	2671.467107

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
234	6	2.2%
254	5	1.9%
269	5	1.9%
233	4	1.5%
243	4	1.5%
282	4	1.5%
226	4	1.5%
211	4	1.5%
212	4	1.5%
197	4	1.5%
239	4	1.5%
177	4	1.5%
204	4	1.5%
219	3	1.1%
230	3	1.1%
199	3	1.1%
303	3	1.1%
229	3	1.1%
245	3	1.1%
240	3	1.1%
250	3	1.1%
201	3	1.1%
258	3	1.1%
274	3	1.1%
309	3	1.1%
Other values (119)	178	65.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
126	1	0.4%
141	1	0.4%
149	2	0.7%
160	1	0.4%
164	1	0.4%
166	1	0.4%
167	1	0.4%
168	1	0.4%
172	1	0.4%
174	1	0.4%

Value	Count	Frequency (%)
564	1	0.4%
417	1	0.4%
409	1	0.4%
407	1	0.4%
394	1	0.4%
360	1	0.4%
354	1	0.4%
353	1	0.4%
341	1	0.4%
340	1	0.4%

fasting_blood_sugar
Boolean

Distinct count	2
Unique (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

0	230
1	40

Frequency Table

Value	Count	Frequency (%)
0	230	85.2%
1	40	14.8%

resting_electrocardiographic_results
Categorical

Distinct count	3
Unique (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

2	137
0	131
1	2

Value	Count	Frequency (%)
2	137	50.7%
0	131	48.5%
1	2	0.7%

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Overview of Unicode Properties

Unique unicode characters	4
Unique unicode categories (?)	2
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
0	401	49.5%
.	270	33.3%
2	137	16.9%
1	2	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	540	66.7%
Other Punctuation	270	33.3%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
0	401	74.3%
2	137	25.4%
1	2	0.4%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
.	270	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	810	100.0%

Most frequent Common characters

Value	Count	Frequency (%)
0	401	49.5%
.	270	33.3%
2	137	16.9%
1	2	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	810	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
0	401	49.5%
.	270	33.3%
2	137	16.9%
1	2	0.2%

maximum_heart_rate_achieved
Real number (ℝ_≥0)

Distinct count	90
Unique (%)	33.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	149.67777777777778
Minimum	71.0
Maximum	202.0
Zeros	0
Zeros (%)	0.0%
Memory size	2.2 KiB

Quantile statistics

Minimum	71
5-th percentile	108
Q1	133
median	153.5
Q3	166
95-th percentile	182
Maximum	202
Range	131
Interquartile range (IQR)	33

Descriptive statistics

Standard deviation	23.16571678
Coefficient of variation (CV)	0.154770582
Kurtosis	-0.1030718853
Mean	149.6777778
Median Absolute Deviation (MAD)	15.5
Skewness	-0.5277366829
Sum	40413
Variance	536.6504337

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
162	10	3.7%
160	9	3.3%
163	8	3.0%
172	7	2.6%
125	7	2.6%
158	6	2.2%
150	6	2.2%
173	6	2.2%
132	6	2.2%
142	6	2.2%
152	6	2.2%
143	5	1.9%
157	5	1.9%
165	5	1.9%
147	5	1.9%
178	5	1.9%
156	5	1.9%
161	5	1.9%
154	5	1.9%
170	5	1.9%
140	5	1.9%
168	5	1.9%
126	4	1.5%
151	4	1.5%
179	4	1.5%
Other values (65)	126	46.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
71	1	0.4%
88	1	0.4%
95	1	0.4%
96	2	0.7%
97	1	0.4%
99	1	0.4%
103	2	0.7%
105	3	1.1%
106	1	0.4%
108	2	0.7%

Value	Count	Frequency (%)
202	1	0.4%
195	1	0.4%
194	1	0.4%
192	1	0.4%
190	1	0.4%
188	1	0.4%
187	1	0.4%
186	2	0.7%
185	1	0.4%
184	1	0.4%

exercise_induced_angina
Boolean

Distinct count	2
Unique (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

0	181
1	89

Frequency Table

Value	Count	Frequency (%)
0	181	67.0%
1	89	33.0%

oldpeak
Real number (ℝ_≥0)

ZEROS

Distinct count	39
Unique (%)	14.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.05
Minimum	0.0
Maximum	6.2
Zeros	85
Zeros (%)	31.5%
Memory size	2.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0.8
Q3	1.6
95-th percentile	3.31
Maximum	6.2
Range	6.2
Interquartile range (IQR)	1.6

Descriptive statistics

Standard deviation	1.145209839
Coefficient of variation (CV)	1.090676038
Kurtosis	1.759316529
Mean	1.05
Median Absolute Deviation (MAD)	0.8
Skewness	1.262893211
Sum	283.5
Variance	1.311505576

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	85	31.5%
1.2	14	5.2%
1.4	13	4.8%
1	12	4.4%
0.6	12	4.4%
0.2	11	4.1%
0.8	11	4.1%
1.6	11	4.1%
1.8	10	3.7%
2	8	3.0%
0.4	8	3.0%
2.6	6	2.2%
0.1	6	2.2%
1.9	5	1.9%
0.5	5	1.9%
1.5	5	1.9%
2.2	4	1.5%
3	4	1.5%
3.6	4	1.5%
2.8	4	1.5%
0.3	3	1.1%
0.9	3	1.1%
2.4	3	1.1%
2.5	2	0.7%
3.2	2	0.7%
Other values (14)	19	7.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	85	31.5%
0.1	6	2.2%
0.2	11	4.1%
0.3	3	1.1%
0.4	8	3.0%
0.5	5	1.9%
0.6	12	4.4%
0.7	1	0.4%
0.8	11	4.1%
0.9	3	1.1%

Value	Count	Frequency (%)
6.2	1	0.4%
5.6	1	0.4%
4.2	2	0.7%
4	2	0.7%
3.8	1	0.4%
3.6	4	1.5%
3.5	1	0.4%
3.4	2	0.7%
3.2	2	0.7%
3.1	1	0.4%

slope
Categorical

Distinct count	3
Unique (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

1	130
2	122
3	18

Value	Count	Frequency (%)
1	130	48.1%
2	122	45.2%
3	18	6.7%

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Overview of Unicode Properties

Unique unicode characters	5
Unique unicode categories (?)	2
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
1	130	16.0%
2	122	15.1%
3	18	2.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	540	66.7%
Other Punctuation	270	33.3%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
0	270	50.0%
1	130	24.1%
2	122	22.6%
3	18	3.3%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
.	270	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	810	100.0%

Most frequent Common characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
1	130	16.0%
2	122	15.1%
3	18	2.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	810	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
1	130	16.0%
2	122	15.1%
3	18	2.2%

number_of_major_vessels
Categorical

Distinct count	4
Unique (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

0	160
1	58
2	33
3	19

Value	Count	Frequency (%)
0	160	59.3%
1	58	21.5%
2	33	12.2%
3	19	7.0%

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Overview of Unicode Properties

Unique unicode characters	5
Unique unicode categories (?)	2
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
0	430	53.1%
.	270	33.3%
1	58	7.2%
2	33	4.1%
3	19	2.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	540	66.7%
Other Punctuation	270	33.3%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
0	430	79.6%
1	58	10.7%
2	33	6.1%
3	19	3.5%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
.	270	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	810	100.0%

Most frequent Common characters

Value	Count	Frequency (%)
0	430	53.1%
.	270	33.3%
1	58	7.2%
2	33	4.1%
3	19	2.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	810	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
0	430	53.1%
.	270	33.3%
1	58	7.2%
2	33	4.1%
3	19	2.3%

thal
Categorical

Distinct count	3
Unique (%)	1.1%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

3	152
7	104
6	14

Value	Count	Frequency (%)
3	152	56.3%
7	104	38.5%
6	14	5.2%

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Overview of Unicode Properties

Unique unicode characters	5
Unique unicode categories (?)	2
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
3	152	18.8%
7	104	12.8%
6	14	1.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	540	66.7%
Other Punctuation	270	33.3%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
0	270	50.0%
3	152	28.1%
7	104	19.3%
6	14	2.6%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
.	270	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	810	100.0%

Most frequent Common characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
3	152	18.8%
7	104	12.8%
6	14	1.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	810	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
.	270	33.3%
0	270	33.3%
3	152	18.8%
7	104	12.8%
6	14	1.7%

target
Boolean

Distinct count	2
Unique (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	2.2 KiB

0	150
1	120

Frequency Table

Value	Count	Frequency (%)
0	150	55.6%
1	120	44.4%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

First rows

	age	sex	chest	resting_blood_pressure	serum_cholestoral	fasting_blood_sugar	resting_electrocardiographic_results	maximum_heart_rate_achieved	exercise_induced_angina	oldpeak	slope	number_of_major_vessels	thal	target
0	70.0	1.0	4.0	130.0	322.0	0.0	2.0	109.0	0.0	2.4	2.0	3.0	3.0	1
1	67.0	0.0	3.0	115.0	564.0	0.0	2.0	160.0	0.0	1.6	2.0	0.0	7.0	0
2	57.0	1.0	2.0	124.0	261.0	0.0	0.0	141.0	0.0	0.3	1.0	0.0	7.0	1
3	64.0	1.0	4.0	128.0	263.0	0.0	0.0	105.0	1.0	0.2	2.0	1.0	7.0	0
4	74.0	0.0	2.0	120.0	269.0	0.0	2.0	121.0	1.0	0.2	1.0	1.0	3.0	0
5	65.0	1.0	4.0	120.0	177.0	0.0	0.0	140.0	0.0	0.4	1.0	0.0	7.0	0
6	56.0	1.0	3.0	130.0	256.0	1.0	2.0	142.0	1.0	0.6	2.0	1.0	6.0	1
7	59.0	1.0	4.0	110.0	239.0	0.0	2.0	142.0	1.0	1.2	2.0	1.0	7.0	1
8	60.0	1.0	4.0	140.0	293.0	0.0	2.0	170.0	0.0	1.2	2.0	2.0	7.0	1
9	63.0	0.0	4.0	150.0	407.0	0.0	2.0	154.0	0.0	4.0	2.0	3.0	7.0	1

Last rows

	age	sex	chest	resting_blood_pressure	serum_cholestoral	fasting_blood_sugar	resting_electrocardiographic_results	maximum_heart_rate_achieved	exercise_induced_angina	oldpeak	slope	number_of_major_vessels	thal	target
260	58.0	0.0	3.0	120.0	340.0	0.0	0.0	172.0	0.0	0.0	1.0	0.0	3.0	0
261	60.0	1.0	4.0	130.0	206.0	0.0	2.0	132.0	1.0	2.4	2.0	2.0	7.0	1
262	58.0	1.0	2.0	120.0	284.0	0.0	2.0	160.0	0.0	1.8	2.0	0.0	3.0	1
263	49.0	1.0	2.0	130.0	266.0	0.0	0.0	171.0	0.0	0.6	1.0	0.0	3.0	0
264	48.0	1.0	2.0	110.0	229.0	0.0	0.0	168.0	0.0	1.0	3.0	0.0	7.0	1
265	52.0	1.0	3.0	172.0	199.0	1.0	0.0	162.0	0.0	0.5	1.0	0.0	7.0	0
266	44.0	1.0	2.0	120.0	263.0	0.0	0.0	173.0	0.0	0.0	1.0	0.0	7.0	0
267	56.0	0.0	2.0	140.0	294.0	0.0	2.0	153.0	0.0	1.3	2.0	0.0	3.0	0
268	57.0	1.0	4.0	140.0	192.0	0.0	0.0	148.0	0.0	0.4	2.0	0.0	6.0	0
269	67.0	1.0	4.0	160.0	286.0	0.0	2.0	108.0	1.0	1.5	2.0	3.0	3.0	1

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent Decimal Number characters

Most frequent Other Punctuation characters

Most occurring scripts

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Decimal Number characters

Most frequent Other Punctuation characters

Most occurring scripts

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Decimal Number characters

Most frequent Other Punctuation characters

Most occurring scripts

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Decimal Number characters

Most frequent Other Punctuation characters

Most occurring scripts

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Decimal Number characters

Most frequent Other Punctuation characters

Most occurring scripts

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows