Pandas Profiling Report

Dataset statistics

Number of variables	10
Number of observations	392
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	30.8 KiB
Average record size in memory	80.3 B

Variable types

Numeric	6
Categorical	4

Alerts

`name` has a high cardinality: 301 distinct values	High cardinality
`mpg` is highly correlated with `cyl` and 7 other fields	High correlation
`cyl` is highly correlated with `mpg` and 6 other fields	High correlation
`displ` is highly correlated with `mpg` and 6 other fields	High correlation
`hp` is highly correlated with `mpg` and 6 other fields	High correlation
`weight` is highly correlated with `mpg` and 6 other fields	High correlation
`accel` is highly correlated with `mpg` and 4 other fields	High correlation
`yr` is highly correlated with `mpg`	High correlation
`origin` is highly correlated with `mpg` and 5 other fields	High correlation
`mfr` is highly correlated with `mpg` and 5 other fields	High correlation
`name` is uniformly distributed	Uniform

Reproduction

Analysis started	2022-09-20 15:16:11.906631
Analysis finished	2022-09-20 15:16:15.454252
Duration	3.55 seconds
Software version	pandas-profiling v3.3.0
Download configuration	config.json

mpg
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	127
Distinct (%)	32.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.44591837

Minimum	9
Maximum	46.6
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.2 KiB

Quantile statistics

Minimum	9
5-th percentile	13
Q1	17
median	22.75
Q3	29
95-th percentile	37
Maximum	46.6
Range	37.6
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	7.805007487
Coefficient of variation (CV)	0.3328940826
Kurtosis	-0.5159934946
Mean	23.44591837
Median Absolute Deviation (MAD)	5.8
Skewness	0.4570923231
Sum	9190.8
Variance	60.91814187
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
13	20	5.1%
14	19	4.8%
18	17	4.3%
15	16	4.1%
26	14	3.6%
16	13	3.3%
19	12	3.1%
24	11	2.8%
28	10	2.6%
22	10	2.6%
Other values (117)	250	63.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
9	1	0.3%
10	2	0.5%
11	4	1.0%
12	6	1.5%
13	20	5.1%
14	19	4.8%
14.5	1	0.3%
15	16	4.1%
15.5	5	1.3%
16	13	3.3%

Value	Count	Frequency (%)
46.6	1	0.3%
44.6	1	0.3%
44.3	1	0.3%
44	1	0.3%
43.4	1	0.3%
43.1	1	0.3%
41.5	1	0.3%
40.8	1	0.3%
39.4	1	0.3%
39.1	1	0.3%

cyl
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	3.2 KiB

4	199
8	103
6	83
3	4
5	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	392
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

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

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	8
2nd row	8
3rd row	8
4th row	8
5th row	8

Common Values

Value	Count	Frequency (%)
4	199	50.8%
8	103	26.3%
6	83	21.2%
3	4	1.0%
5	3	0.8%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
4	199	50.8%
8	103	26.3%
6	83	21.2%
3	4	1.0%
5	3	0.8%

Most occurring characters

Value	Count	Frequency (%)
4	199	50.8%
8	103	26.3%
6	83	21.2%
3	4	1.0%
5	3	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	392	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	199	50.8%
8	103	26.3%
6	83	21.2%
3	4	1.0%
5	3	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	392	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	199	50.8%
8	103	26.3%
6	83	21.2%
3	4	1.0%
5	3	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	392	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	199	50.8%
8	103	26.3%
6	83	21.2%
3	4	1.0%
5	3	0.8%

displ
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	81
Distinct (%)	20.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	194.4119898

Minimum	68
Maximum	455
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.2 KiB

Quantile statistics

Minimum	68
5-th percentile	85
Q1	105
median	151
Q3	275.75
95-th percentile	400
Maximum	455
Range	387
Interquartile range (IQR)	170.75

Descriptive statistics

Standard deviation	104.6440039
Coefficient of variation (CV)	0.5382590036
Kurtosis	-0.7783169302
Mean	194.4119898
Median Absolute Deviation (MAD)	61
Skewness	0.7016690997
Sum	76209.5
Variance	10950.36755
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
97	21	5.4%
350	18	4.6%
98	17	4.3%
318	17	4.3%
250	17	4.3%
140	15	3.8%
400	13	3.3%
225	13	3.3%
91	12	3.1%
302	11	2.8%
Other values (71)	238	60.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
68	1	0.3%
70	3	0.8%
71	2	0.5%
72	1	0.3%
76	1	0.3%
78	1	0.3%
79	6	1.5%
80	1	0.3%
81	1	0.3%
83	1	0.3%

Value	Count	Frequency (%)
455	3	0.8%
454	1	0.3%
440	2	0.5%
429	3	0.8%
400	13	3.3%
390	1	0.3%
383	2	0.5%
360	4	1.0%
351	8	2.0%
350	18	4.6%

hp
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	93
Distinct (%)	23.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	104.4693878

Minimum	46
Maximum	230
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.2 KiB

Quantile statistics

Minimum	46
5-th percentile	60.55
Q1	75
median	93.5
Q3	126
95-th percentile	180
Maximum	230
Range	184
Interquartile range (IQR)	51

Descriptive statistics

Standard deviation	38.49115993
Coefficient of variation (CV)	0.3684443908
Kurtosis	0.6969469997
Mean	104.4693878
Median Absolute Deviation (MAD)	19.5
Skewness	1.087326282
Sum	40952
Variance	1481.569393
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
150	22	5.6%
90	20	5.1%
88	19	4.8%
110	18	4.6%
100	17	4.3%
75	14	3.6%
95	14	3.6%
105	12	3.1%
70	12	3.1%
67	12	3.1%
Other values (83)	232	59.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
46	2	0.5%
48	3	0.8%
49	1	0.3%
52	4	1.0%
53	2	0.5%
54	1	0.3%
58	2	0.5%
60	5	1.3%
61	1	0.3%
62	2	0.5%

Value	Count	Frequency (%)
230	1	0.3%
225	3	0.8%
220	1	0.3%
215	3	0.8%
210	1	0.3%
208	1	0.3%
200	1	0.3%
198	2	0.5%
193	1	0.3%
190	3	0.8%

weight
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	346
Distinct (%)	88.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2977.584184

Minimum	1613
Maximum	5140
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.2 KiB

Quantile statistics

Minimum	1613
5-th percentile	1931.6
Q1	2225.25
median	2803.5
Q3	3614.75
95-th percentile	4464
Maximum	5140
Range	3527
Interquartile range (IQR)	1389.5

Descriptive statistics

Standard deviation	849.40256
Coefficient of variation (CV)	0.2852656743
Kurtosis	-0.8092593883
Mean	2977.584184
Median Absolute Deviation (MAD)	639.5
Skewness	0.5195856741
Sum	1167213
Variance	721484.709
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1985	4	1.0%
2130	4	1.0%
2125	3	0.8%
2720	3	0.8%
2945	3	0.8%
2300	3	0.8%
2265	3	0.8%
2155	3	0.8%
2408	2	0.5%
2164	2	0.5%
Other values (336)	362	92.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1613	1	0.3%
1649	1	0.3%
1755	1	0.3%
1760	1	0.3%
1773	1	0.3%
1795	2	0.5%
1800	2	0.5%
1825	2	0.5%
1834	1	0.3%
1835	1	0.3%

Value	Count	Frequency (%)
5140	1	0.3%
4997	1	0.3%
4955	1	0.3%
4952	1	0.3%
4951	1	0.3%
4906	1	0.3%
4746	1	0.3%
4735	1	0.3%
4732	1	0.3%
4699	1	0.3%

accel
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	95
Distinct (%)	24.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15.54132653

Minimum	8
Maximum	24.8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.2 KiB

Quantile statistics

Minimum	8
5-th percentile	11.255
Q1	13.775
median	15.5
Q3	17.025
95-th percentile	20.235
Maximum	24.8
Range	16.8
Interquartile range (IQR)	3.25

Descriptive statistics

Standard deviation	2.758864119
Coefficient of variation (CV)	0.1775179303
Kurtosis	0.4442335534
Mean	15.54132653
Median Absolute Deviation (MAD)	1.7
Skewness	0.2915869257
Sum	6092.2
Variance	7.611331228
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
14.5	23	5.9%
15.5	21	5.4%
14	16	4.1%
16	16	4.1%
13.5	15	3.8%
15	14	3.6%
16.5	13	3.3%
17	13	3.3%
13	12	3.1%
19	11	2.8%
Other values (85)	238	60.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
8	1	0.3%
8.5	2	0.5%
9	1	0.3%
9.5	2	0.5%
10	4	1.0%
10.5	1	0.3%
11	7	1.8%
11.1	1	0.3%
11.2	1	0.3%
11.3	1	0.3%

Value	Count	Frequency (%)
24.8	1	0.3%
24.6	1	0.3%
23.7	1	0.3%
23.5	1	0.3%
22.2	2	0.5%
22.1	1	0.3%
21.9	1	0.3%
21.8	1	0.3%
21.7	1	0.3%
21.5	1	0.3%

yr
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	13
Distinct (%)	3.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	75.97959184

Minimum	70
Maximum	82
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.2 KiB

Quantile statistics

Minimum	70
5-th percentile	70
Q1	73
median	76
Q3	79
95-th percentile	82
Maximum	82
Range	12
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.683736544
Coefficient of variation (CV)	0.04848323681
Kurtosis	-1.16744622
Mean	75.97959184
Median Absolute Deviation (MAD)	3
Skewness	0.01968829963
Sum	29784
Variance	13.56991492
Monotonicity	Increasing

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
73	40	10.2%
78	36	9.2%
76	34	8.7%
75	30	7.7%
82	30	7.7%
70	29	7.4%
79	29	7.4%
72	28	7.1%
77	28	7.1%
81	28	7.1%
Other values (3)	80	20.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
70	29	7.4%
71	27	6.9%
72	28	7.1%
73	40	10.2%
74	26	6.6%
75	30	7.7%
76	34	8.7%
77	28	7.1%
78	36	9.2%
79	29	7.4%

Value	Count	Frequency (%)
82	30	7.7%
81	28	7.1%
80	27	6.9%
79	29	7.4%
78	36	9.2%
77	28	7.1%
76	34	8.7%
75	30	7.7%
74	26	6.6%
73	40	10.2%

origin
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Memory size	3.2 KiB

North America	245
Asia	79
Europe	68

Length

Max length	13
Median length	13
Mean length	9.971938776
Min length	4

Characters and Unicode

Total characters	3909
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

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

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	North America
2nd row	North America
3rd row	North America
4th row	North America
5th row	North America

Common Values

Value	Count	Frequency (%)
North America	245	62.5%
Asia	79	20.2%
Europe	68	17.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
north	245	38.5%
america	245	38.5%
asia	79	12.4%
europe	68	10.7%

Most occurring characters

Value	Count	Frequency (%)
r	558	14.3%
A	324	8.3%
i	324	8.3%
a	324	8.3%
o	313	8.0%
e	313	8.0%
N	245	6.3%
t	245	6.3%
h	245	6.3%
	245	6.3%
Other values (6)	773	19.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3027	77.4%
Uppercase Letter	637	16.3%
Space Separator	245	6.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	558	18.4%
i	324	10.7%
a	324	10.7%
o	313	10.3%
e	313	10.3%
t	245	8.1%
h	245	8.1%
m	245	8.1%
c	245	8.1%
s	79	2.6%
Other values (2)	136	4.5%

Uppercase Letter

Value	Count	Frequency (%)
A	324	50.9%
N	245	38.5%
E	68	10.7%

Space Separator

Value	Count	Frequency (%)
	245	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3664	93.7%
Common	245	6.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	558	15.2%
A	324	8.8%
i	324	8.8%
a	324	8.8%
o	313	8.5%
e	313	8.5%
N	245	6.7%
t	245	6.7%
h	245	6.7%
m	245	6.7%
Other values (5)	528	14.4%

Common

Value	Count	Frequency (%)
	245	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3909	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	558	14.3%
A	324	8.3%
i	324	8.3%
a	324	8.3%
o	313	8.0%
e	313	8.0%
N	245	6.3%
t	245	6.3%
h	245	6.3%
	245	6.3%
Other values (6)	773	19.8%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	301
Distinct (%)	76.8%
Missing	0
Missing (%)	0.0%
Memory size	3.2 KiB

amc matador	5
ford pinto	5
toyota corolla	5
toyota corona	4
amc hornet	4
Other values (296)	369

Length

Max length	36
Median length	28
Mean length	16.12244898
Min length	6

Characters and Unicode

Total characters	6320
Distinct characters	45
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

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

Unique

Unique	245 ?
Unique (%)	62.5%

Sample

1st row	chevrolet chevelle malibu
2nd row	buick skylark 320
3rd row	plymouth satellite
4th row	amc rebel sst
5th row	ford torino

Common Values

Value	Count	Frequency (%)
amc matador	5	1.3%
ford pinto	5	1.3%
toyota corolla	5	1.3%
toyota corona	4	1.0%
amc hornet	4	1.0%
chevrolet chevette	4	1.0%
chevrolet impala	4	1.0%
amc gremlin	4	1.0%
peugeot 504	4	1.0%
ford maverick	4	1.0%
Other values (291)	349	89.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ford	48	4.7%
chevrolet	43	4.2%
plymouth	31	3.0%
sw	28	2.7%
dodge	28	2.7%
amc	27	2.6%
toyota	25	2.4%
datsun	23	2.2%
custom	18	1.8%
buick	17	1.7%
Other values (302)	737	71.9%

Most occurring characters

Value	Count	Frequency (%)
	633	10.0%
o	523	8.3%
a	494	7.8%
e	413	6.5%
r	381	6.0%
t	379	6.0%
c	346	5.5%
l	327	5.2%
d	261	4.1%
i	252	4.0%
Other values (35)	2311	36.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5288	83.7%
Space Separator	633	10.0%
Decimal Number	307	4.9%
Open Punctuation	36	0.6%
Close Punctuation	36	0.6%
Dash Punctuation	10	0.2%
Other Punctuation	8	0.1%
Math Symbol	2	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	523	9.9%
a	494	9.3%
e	413	7.8%
r	381	7.2%
t	379	7.2%
c	346	6.5%
l	327	6.2%
d	261	4.9%
i	252	4.8%
s	246	4.7%
Other values (16)	1666	31.5%

Decimal Number

Value	Count	Frequency (%)
0	100	32.6%
1	55	17.9%
2	48	15.6%
4	26	8.5%
5	25	8.1%
3	15	4.9%
6	13	4.2%
9	11	3.6%
8	10	3.3%
7	4	1.3%

Other Punctuation

Value	Count	Frequency (%)
.	3	37.5%
/	3	37.5%
@	1	12.5%
'	1	12.5%

Space Separator

Value	Count	Frequency (%)
	633	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	36	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	36	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	10	100.0%

Math Symbol

Value	Count	Frequency (%)
+	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5288	83.7%
Common	1032	16.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	523	9.9%
a	494	9.3%
e	413	7.8%
r	381	7.2%
t	379	7.2%
c	346	6.5%
l	327	6.2%
d	261	4.9%
i	252	4.8%
s	246	4.7%
Other values (16)	1666	31.5%

Common

Value	Count	Frequency (%)
	633	61.3%
0	100	9.7%
1	55	5.3%
2	48	4.7%
(	36	3.5%
)	36	3.5%
4	26	2.5%
5	25	2.4%
3	15	1.5%
6	13	1.3%
Other values (9)	45	4.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6320	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	633	10.0%
o	523	8.3%
a	494	7.8%
e	413	6.5%
r	381	6.0%
t	379	6.0%
c	346	5.5%
l	327	5.2%
d	261	4.1%
i	252	4.0%
Other values (35)	2311	36.6%

mfr
Categorical

HIGH CORRELATION

Distinct	30
Distinct (%)	7.7%
Missing	0
Missing (%)	0.0%
Memory size	3.2 KiB

ford	48
chevrolet	47
plymouth	31
dodge	28
amc	27
Other values (25)	211

Length

Max length	10
Median length	8
Mean length	6.209183673
Min length	2

Characters and Unicode

Total characters	2434
Distinct characters	23
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

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

Unique

Unique	4 ?
Unique (%)	1.0%

Sample

1st row	chevrolet
2nd row	buick
3rd row	plymouth
4th row	amc
5th row	ford

Common Values

Value	Count	Frequency (%)
ford	48	12.2%
chevrolet	47	12.0%
plymouth	31	7.9%
dodge	28	7.1%
amc	27	6.9%
toyota	26	6.6%
datsun	23	5.9%
volkswagen	22	5.6%
buick	17	4.3%
pontiac	16	4.1%
Other values (20)	107	27.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ford	48	12.2%
chevrolet	47	12.0%
plymouth	31	7.9%
dodge	28	7.1%
amc	27	6.9%
toyota	26	6.6%
datsun	23	5.9%
volkswagen	22	5.6%
buick	17	4.3%
pontiac	16	4.1%
Other values (20)	107	27.3%

Most occurring characters

Value	Count	Frequency (%)
o	301	12.4%
e	203	8.3%
t	189	7.8%
a	187	7.7%
d	174	7.1%
l	143	5.9%
r	141	5.8%
c	132	5.4%
u	109	4.5%
h	99	4.1%
Other values (13)	756	31.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2434	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	301	12.4%
e	203	8.3%
t	189	7.8%
a	187	7.7%
d	174	7.1%
l	143	5.9%
r	141	5.8%
c	132	5.4%
u	109	4.5%
h	99	4.1%
Other values (13)	756	31.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2434	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	301	12.4%
e	203	8.3%
t	189	7.8%
a	187	7.7%
d	174	7.1%
l	143	5.9%
r	141	5.8%
c	132	5.4%
u	109	4.5%
h	99	4.1%
Other values (13)	756	31.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2434	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	301	12.4%
e	203	8.3%
t	189	7.8%
a	187	7.7%
d	174	7.1%
l	143	5.9%
r	141	5.8%
c	132	5.4%
u	109	4.5%
h	99	4.1%
Other values (13)	756	31.1%

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.

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.

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.

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.

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.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	mpg	cyl	displ	hp	weight	accel	yr	origin	name	mfr
0	18.0	8	307.0	130	3504	12.0	70	North America	chevrolet chevelle malibu	chevrolet
1	15.0	8	350.0	165	3693	11.5	70	North America	buick skylark 320	buick
2	18.0	8	318.0	150	3436	11.0	70	North America	plymouth satellite	plymouth
3	16.0	8	304.0	150	3433	12.0	70	North America	amc rebel sst	amc
4	17.0	8	302.0	140	3449	10.5	70	North America	ford torino	ford
5	15.0	8	429.0	198	4341	10.0	70	North America	ford galaxie 500	ford
6	14.0	8	454.0	220	4354	9.0	70	North America	chevrolet impala	chevrolet
7	14.0	8	440.0	215	4312	8.5	70	North America	plymouth fury iii	plymouth
8	14.0	8	455.0	225	4425	10.0	70	North America	pontiac catalina	pontiac
9	15.0	8	390.0	190	3850	8.5	70	North America	amc ambassador dpl	amc

Last rows

	mpg	cyl	displ	hp	weight	accel	yr	origin	name	mfr
382	26.0	4	156.0	92	2585	14.5	82	North America	chrysler lebaron medallion	chrysler
383	22.0	6	232.0	112	2835	14.7	82	North America	ford granada l	ford
384	32.0	4	144.0	96	2665	13.9	82	Asia	toyota celica gt	toyota
385	36.0	4	135.0	84	2370	13.0	82	North America	dodge charger 2.2	dodge
386	27.0	4	151.0	90	2950	17.3	82	North America	chevrolet camaro	chevrolet
387	27.0	4	140.0	86	2790	15.6	82	North America	ford mustang gl	ford
388	44.0	4	97.0	52	2130	24.6	82	Europe	vw pickup	volkswagen
389	32.0	4	135.0	84	2295	11.6	82	North America	dodge rampage	dodge
390	28.0	4	120.0	79	2625	18.6	82	North America	ford ranger	ford
391	31.0	4	119.0	82	2720	19.4	82	North America	chevy s-10	chevrolet

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Other Punctuation

Space Separator

Open Punctuation

Close Punctuation

Dash Punctuation

Math Symbol

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows