Overview

Dataset statistics

Number of variables14
Number of observations45726
Missing cells29703
Missing cells (%)4.6%
Duplicate rows10
Duplicate rows (%)< 0.1%
Total size in memory21.6 MiB
Average record size in memory494.8 B

Variable types

CAT7
NUM5
BOOL1
DATE1

Warnings

source has constant value "45726" Constant
Dataset has 10 (< 0.1%) duplicate rows Duplicates
name has a high cardinality: 45716 distinct values High cardinality
recclass has a high cardinality: 466 distinct values High cardinality
GeoLocation has a high cardinality: 17100 distinct values High cardinality
reclat_city is highly correlated with reclatHigh correlation
reclat is highly correlated with reclat_cityHigh correlation
reclat has 7315 (16.0%) missing values Missing
reclong has 7315 (16.0%) missing values Missing
GeoLocation has 7315 (16.0%) missing values Missing
reclat_city has 7315 (16.0%) missing values Missing
mass (g) is highly skewed (γ1 = 76.91847245) Skewed
name is uniformly distributed Uniform
reclat has 6438 (14.1%) zeros Zeros
reclong has 6214 (13.6%) zeros Zeros

Reproduction

Analysis started2020-10-25 20:17:26.819414
Analysis finished2020-10-25 20:17:36.741684
Duration9.92 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct45716
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size357.4 KiB
Aarhus
 
2
Adzhi-Bogdo (stone)
 
2
Aguila Blanca
 
2
Acapulco
 
2
Adhi Kot
 
2
Other values (45711)
45716 
ValueCountFrequency (%) 
Aarhus2< 0.1%
 
Adzhi-Bogdo (stone)2< 0.1%
 
Aguila Blanca2< 0.1%
 
Acapulco2< 0.1%
 
Adhi Kot2< 0.1%
 
Achiras2< 0.1%
 
Abee2< 0.1%
 
Aguada2< 0.1%
 
Agen2< 0.1%
 
Aachen2< 0.1%
 
LaPaz Icefield 035571< 0.1%
 
Yamato 7921491< 0.1%
 
Ourique1< 0.1%
 
Jiddat al Harasis 0251< 0.1%
 
Elephant Moraine 907731< 0.1%
 
Larkman Nunatak 068781< 0.1%
 
Queen Alexandra Range 933621< 0.1%
 
Northwest Africa 74761< 0.1%
 
Yamato 9824011< 0.1%
 
Northwest Africa 32621< 0.1%
 
Elephant Moraine 901101< 0.1%
 
Northwest Africa 16851< 0.1%
 
Yamato 7910401< 0.1%
 
Northwest Africa 69981< 0.1%
 
Yamato 745611< 0.1%
 
Other values (45691)4569199.9%
 
2020-10-25T20:17:36.991665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique45706 ?
Unique (%)> 99.9%
2020-10-25T20:17:37.219670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length28
Median length19
Mean length17.78248699
Min length2

Overview of Unicode Properties

Unique unicode characters96
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
8103210.0%
 
a727158.9%
 
e481675.9%
 
n383924.7%
 
0349434.3%
 
r330974.1%
 
i326584.0%
 
l318733.9%
 
t308983.8%
 
o304283.7%
 
9244443.0%
 
8221792.7%
 
1219862.7%
 
s209722.6%
 
2198392.4%
 
7193472.4%
 
3173792.1%
 
4160012.0%
 
5148121.8%
 
6144851.8%
 
A141201.7%
 
m123931.5%
 
f123451.5%
 
u121251.5%
 
h113981.4%
 
Other values (71)12509415.4%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter44094954.2%
 
Decimal Number20541525.3%
 
Uppercase Letter8494210.4%
 
Space Separator8103210.0%
 
Open Punctuation295< 0.1%
 
Close Punctuation295< 0.1%
 
Dash Punctuation98< 0.1%
 
Other Punctuation96< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A1412016.6%
 
M1117313.2%
 
R75998.9%
 
Y73278.6%
 
N57966.8%
 
H56766.7%
 
G46825.5%
 
L46305.5%
 
D37774.4%
 
Q34784.1%
 
E31713.7%
 
P28613.4%
 
C28113.3%
 
S18552.2%
 
I16812.0%
 
F9471.1%
 
J8581.0%
 
U5810.7%
 
B4440.5%
 
T4310.5%
 
K3120.4%
 
W2690.3%
 
V2060.2%
 
O1260.1%
 
Ö630.1%
 
Other values (6)680.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
a7271516.5%
 
e4816710.9%
 
n383928.7%
 
r330977.5%
 
i326587.4%
 
l318737.2%
 
t308987.0%
 
o304286.9%
 
s209724.8%
 
m123932.8%
 
f123452.8%
 
u121252.7%
 
h113982.6%
 
c98612.2%
 
d80781.8%
 
g75321.7%
 
w66971.5%
 
k44041.0%
 
p43311.0%
 
v37130.8%
 
x36760.8%
 
y19530.4%
 
z17830.4%
 
b8310.2%
 
é204< 0.1%
 
Other values (24)4250.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
81032100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-98100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(295100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)295100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
'6769.8%
 
.2930.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03494317.0%
 
92444411.9%
 
82217910.8%
 
12198610.7%
 
2198399.7%
 
7193479.4%
 
3173798.5%
 
4160017.8%
 
5148127.2%
 
6144857.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin52589164.7%
 
Common28723135.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
a7271513.8%
 
e481679.2%
 
n383927.3%
 
r330976.3%
 
i326586.2%
 
l318736.1%
 
t308985.9%
 
o304285.8%
 
s209724.0%
 
A141202.7%
 
m123932.4%
 
f123452.3%
 
u121252.3%
 
h113982.2%
 
M111732.1%
 
c98611.9%
 
d80781.5%
 
R75991.4%
 
g75321.4%
 
Y73271.4%
 
w66971.3%
 
N57961.1%
 
H56761.1%
 
G46820.9%
 
L46300.9%
 
Other values (55)452598.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
8103228.2%
 
03494312.2%
 
9244448.5%
 
8221797.7%
 
1219867.7%
 
2198396.9%
 
7193476.7%
 
3173796.1%
 
4160015.6%
 
5148125.2%
 
6144855.0%
 
(2950.1%
 
)2950.1%
 
-98< 0.1%
 
'67< 0.1%
 
.29< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII81263899.9%
 
None4840.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
8103210.0%
 
a727158.9%
 
e481675.9%
 
n383924.7%
 
0349434.3%
 
r330974.1%
 
i326584.0%
 
l318733.9%
 
t308983.8%
 
o304283.7%
 
9244443.0%
 
8221792.7%
 
1219862.7%
 
s209722.6%
 
2198392.4%
 
7193472.4%
 
3173792.1%
 
4160012.0%
 
5148121.8%
 
6144851.8%
 
A141201.7%
 
m123931.5%
 
f123451.5%
 
u121251.5%
 
h113981.4%
 
Other values (43)12461015.3%
 

Most frequent None characters

ValueCountFrequency (%) 
é20442.1%
 
ş12525.8%
 
Ö6313.0%
 
ö112.3%
 
á112.3%
 
ä102.1%
 
ó81.7%
 
ñ81.7%
 
ü81.7%
 
ã51.0%
 
ú30.6%
 
š30.6%
 
å30.6%
 
í30.6%
 
ï20.4%
 
ê20.4%
 
ø20.4%
 
ł20.4%
 
ù20.4%
 
Ç10.2%
 
â10.2%
 
É10.2%
 
Ł10.2%
 
è10.2%
 
ë10.2%
 
Other values (3)30.6%
 

id
Real number (ℝ≥0)

Distinct45716
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26883.9062
Minimum1
Maximum57458
Zeros0
Zeros (%)0.0%
Memory size357.4 KiB
2020-10-25T20:17:37.461522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2388.75
Q112681.25
median24256.5
Q340653.5
95-th percentile54890.75
Maximum57458
Range57457
Interquartile range (IQR)27972.25

Descriptive statistics

Standard deviation16863.44557
Coefficient of variation (CV)0.6272691713
Kurtosis-1.160130804
Mean26883.9062
Median Absolute Deviation (MAD)13264
Skewness0.2665300704
Sum1229293495
Variance284375796.4
MonotocityNot monotonic
2020-10-25T20:17:37.668870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
4172< 0.1%
 
3982< 0.1%
 
12< 0.1%
 
62< 0.1%
 
3922< 0.1%
 
3702< 0.1%
 
3792< 0.1%
 
22< 0.1%
 
3902< 0.1%
 
102< 0.1%
 
12901< 0.1%
 
197151< 0.1%
 
74331< 0.1%
 
53841< 0.1%
 
279111< 0.1%
 
299561< 0.1%
 
33391< 0.1%
 
20471< 0.1%
 
176661< 0.1%
 
238091< 0.1%
 
217601< 0.1%
 
483811< 0.1%
 
463321< 0.1%
 
360911< 0.1%
 
340421< 0.1%
 
Other values (45691)4569199.9%
 
ValueCountFrequency (%) 
12< 0.1%
 
22< 0.1%
 
41< 0.1%
 
51< 0.1%
 
62< 0.1%
 
71< 0.1%
 
81< 0.1%
 
91< 0.1%
 
102< 0.1%
 
111< 0.1%
 
ValueCountFrequency (%) 
574581< 0.1%
 
574571< 0.1%
 
574561< 0.1%
 
574551< 0.1%
 
574541< 0.1%
 
574531< 0.1%
 
574361< 0.1%
 
574351< 0.1%
 
574341< 0.1%
 
574331< 0.1%
 

nametype
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size357.4 KiB
Valid
45651 
Relict
 
75
ValueCountFrequency (%) 
Valid4565199.8%
 
Relict750.2%
 
2020-10-25T20:17:37.875440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-25T20:17:37.974331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-25T20:17:38.082494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length5
Mean length5.001640205
Min length5

Overview of Unicode Properties

Unique unicode characters9
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
l4572620.0%
 
i4572620.0%
 
V4565120.0%
 
a4565120.0%
 
d4565120.0%
 
R75< 0.1%
 
e75< 0.1%
 
c75< 0.1%
 
t75< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter18297980.0%
 
Uppercase Letter4572620.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
V4565199.8%
 
R750.2%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
l4572625.0%
 
i4572625.0%
 
a4565124.9%
 
d4565124.9%
 
e75< 0.1%
 
c75< 0.1%
 
t75< 0.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin228705100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
l4572620.0%
 
i4572620.0%
 
V4565120.0%
 
a4565120.0%
 
d4565120.0%
 
R75< 0.1%
 
e75< 0.1%
 
c75< 0.1%
 
t75< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII228705100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
l4572620.0%
 
i4572620.0%
 
V4565120.0%
 
a4565120.0%
 
d4565120.0%
 
R75< 0.1%
 
e75< 0.1%
 
c75< 0.1%
 
t75< 0.1%
 

recclass
Categorical

HIGH CARDINALITY

Distinct466
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size357.4 KiB
L6
8287 
H5
7143 
L5
4797 
H6
4529 
H4
4211 
Other values (461)
16759 
ValueCountFrequency (%) 
L6828718.1%
 
H5714315.6%
 
L5479710.5%
 
H645299.9%
 
H442119.2%
 
LL527666.0%
 
LL620434.5%
 
L412532.7%
 
H4/54280.9%
 
CM24160.9%
 
H33860.8%
 
L33650.8%
 
CO33350.7%
 
Ureilite3000.7%
 
Iron, IIIAB2850.6%
 
LL42680.6%
 
CV32560.6%
 
Diogenite2410.5%
 
Howardite2400.5%
 
LL2250.5%
 
Eucrite2210.5%
 
Eucrite-pmict2070.5%
 
E32060.5%
 
H5/61930.4%
 
Mesosiderite1370.3%
 
Other values (441)598813.1%
 
2020-10-25T20:17:38.275493image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique145 ?
Unique (%)0.3%
2020-10-25T20:17:38.484858image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length26
Median length2
Mean length3.052530289
Min length1

Overview of Unicode Properties

Unique unicode characters62
Unique unicode categories9 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
L2846720.4%
 
H1839613.2%
 
51641911.8%
 
61613211.6%
 
469305.0%
 
e39722.8%
 
i38342.7%
 
r36482.6%
 
t33272.4%
 
332782.3%
 
I27532.0%
 
n25201.8%
 
o24581.8%
 
-18351.3%
 
C17851.3%
 
c17671.3%
 
17471.3%
 
u14691.1%
 
a14091.0%
 
E12610.9%
 
/11740.8%
 
.10640.8%
 
,10310.7%
 
l10160.7%
 
A9850.7%
 
Other values (37)109037.8%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter5779341.4%
 
Decimal Number4411831.6%
 
Lowercase Letter2992621.4%
 
Other Punctuation32932.4%
 
Dash Punctuation18351.3%
 
Space Separator17471.3%
 
Math Symbol3200.2%
 
Open Punctuation2740.2%
 
Close Punctuation2740.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
L2846749.3%
 
H1839631.8%
 
I27534.8%
 
C17853.1%
 
E12612.2%
 
A9851.7%
 
M9131.6%
 
B7541.3%
 
O5420.9%
 
V3500.6%
 
R3500.6%
 
U3340.6%
 
D2850.5%
 
K2310.4%
 
P1480.3%
 
G1390.2%
 
S550.1%
 
W25< 0.1%
 
F19< 0.1%
 
X1< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
51641937.2%
 
61613236.6%
 
4693015.7%
 
332787.4%
 
26461.5%
 
72510.6%
 
82160.5%
 
91110.3%
 
11000.2%
 
0350.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e397213.3%
 
i383412.8%
 
r364812.2%
 
t332711.1%
 
n25208.4%
 
o24588.2%
 
c17675.9%
 
u14694.9%
 
a14094.7%
 
l10163.4%
 
m7862.6%
 
s7132.4%
 
d7082.4%
 
g6712.2%
 
p5581.9%
 
b3531.2%
 
h3121.0%
 
w2480.8%
 
k630.2%
 
x540.2%
 
f310.1%
 
v9< 0.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-1835100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/117435.7%
 
.106432.3%
 
,103131.3%
 
?240.7%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1747100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(274100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)274100.0%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
~31999.7%
 
<10.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin8771962.8%
 
Common5186137.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
L2846732.5%
 
H1839621.0%
 
e39724.5%
 
i38344.4%
 
r36484.2%
 
t33273.8%
 
I27533.1%
 
n25202.9%
 
o24582.8%
 
C17852.0%
 
c17672.0%
 
u14691.7%
 
a14091.6%
 
E12611.4%
 
l10161.2%
 
A9851.1%
 
M9131.0%
 
m7860.9%
 
B7540.9%
 
s7130.8%
 
d7080.8%
 
g6710.8%
 
p5580.6%
 
O5420.6%
 
b3530.4%
 
Other values (17)26543.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
51641931.7%
 
61613231.1%
 
4693013.4%
 
332786.3%
 
-18353.5%
 
17473.4%
 
/11742.3%
 
.10642.1%
 
,10312.0%
 
26461.2%
 
~3190.6%
 
(2740.5%
 
)2740.5%
 
72510.5%
 
82160.4%
 
91110.2%
 
11000.2%
 
0350.1%
 
?24< 0.1%
 
<1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII139580100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
L2846720.4%
 
H1839613.2%
 
51641911.8%
 
61613211.6%
 
469305.0%
 
e39722.8%
 
i38342.7%
 
r36482.6%
 
t33272.4%
 
332782.3%
 
I27532.0%
 
n25201.8%
 
o24581.8%
 
-18351.3%
 
C17851.3%
 
c17671.3%
 
17471.3%
 
u14691.1%
 
a14091.0%
 
E12610.9%
 
/11740.8%
 
.10640.8%
 
,10310.7%
 
l10160.7%
 
A9850.7%
 
Other values (37)109037.8%
 

mass (g)
Real number (ℝ≥0)

SKEWED

Distinct12576
Distinct (%)27.6%
Missing131
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean13278.42646
Minimum0
Maximum60000000
Zeros19
Zeros (%)< 0.1%
Memory size357.4 KiB
2020-10-25T20:17:38.686912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q17.2
median32.61
Q3202.9
95-th percentile4000
Maximum60000000
Range60000000
Interquartile range (IQR)195.7

Descriptive statistics

Standard deviation574926.0121
Coefficient of variation (CV)43.2977517
Kurtosis6798.398388
Mean13278.42646
Median Absolute Deviation (MAD)30.51
Skewness76.91847245
Sum605429854.6
Variance3.305399193e+11
MonotocityNot monotonic
2020-10-25T20:17:38.917074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.31710.4%
 
1.21400.3%
 
1.41380.3%
 
2.11300.3%
 
2.41260.3%
 
1.61200.3%
 
0.51190.3%
 
1.11160.3%
 
3.81140.2%
 
0.71110.2%
 
1.51110.2%
 
3.11090.2%
 
1.71090.2%
 
3.21090.2%
 
31080.2%
 
0.91080.2%
 
0.61080.2%
 
0.81070.2%
 
1.81040.2%
 
2.51030.2%
 
2.71020.2%
 
1960.2%
 
2960.2%
 
3.6960.2%
 
4.2950.2%
 
Other values (12551)4274993.5%
 
(Missing)1310.3%
 
ValueCountFrequency (%) 
019< 0.1%
 
0.012< 0.1%
 
0.0131< 0.1%
 
0.021< 0.1%
 
0.031< 0.1%
 
0.041< 0.1%
 
0.051< 0.1%
 
0.061< 0.1%
 
0.073< 0.1%
 
0.082< 0.1%
 
ValueCountFrequency (%) 
600000001< 0.1%
 
582000001< 0.1%
 
500000001< 0.1%
 
300000001< 0.1%
 
280000001< 0.1%
 
260000001< 0.1%
 
243000001< 0.1%
 
240000001< 0.1%
 
230000001< 0.1%
 
220000001< 0.1%
 

fall
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size357.4 KiB
Found
44609 
Fell
 
1117
ValueCountFrequency (%) 
Found4460997.6%
 
Fell11172.4%
 
2020-10-25T20:17:39.246524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-25T20:17:39.350737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-25T20:17:39.461638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length5
Mean length4.975571885
Min length4

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
F4572620.1%
 
o4460919.6%
 
u4460919.6%
 
n4460919.6%
 
d4460919.6%
 
l22341.0%
 
e11170.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter18178779.9%
 
Uppercase Letter4572620.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
F45726100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
o4460924.5%
 
u4460924.5%
 
n4460924.5%
 
d4460924.5%
 
l22341.2%
 
e11170.6%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin227513100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
F4572620.1%
 
o4460919.6%
 
u4460919.6%
 
n4460919.6%
 
d4460919.6%
 
l22341.0%
 
e11170.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII227513100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
F4572620.1%
 
o4460919.6%
 
u4460919.6%
 
n4460919.6%
 
d4460919.6%
 
l22341.0%
 
e11170.5%
 

year
Date

Distinct245
Distinct (%)0.5%
Missing312
Missing (%)0.7%
Memory size357.4 KiB
Minimum1688-01-01 00:00:00
Maximum2101-01-01 00:00:00
2020-10-25T20:17:39.627070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-25T20:17:39.864183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

reclat
Real number (ℝ)

HIGH CORRELATION
MISSING
ZEROS

Distinct12738
Distinct (%)33.2%
Missing7315
Missing (%)16.0%
Infinite0
Infinite (%)0.0%
Mean-39.10709514
Minimum-87.36667
Maximum81.16667
Zeros6438
Zeros (%)14.1%
Memory size357.4 KiB
2020-10-25T20:17:40.100966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-87.36667
5-th percentile-84.35476
Q1-76.71377
median-71.5
Q30
95-th percentile34.494325
Maximum81.16667
Range168.53334
Interquartile range (IQR)76.71377

Descriptive statistics

Standard deviation46.38601095
Coefficient of variation (CV)-1.186127755
Kurtosis-1.476865084
Mean-39.10709514
Median Absolute Deviation (MAD)12.76459
Skewness0.4913157316
Sum-1502142.632
Variance2151.662012
MonotocityNot monotonic
2020-10-25T20:17:40.303467image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0643814.1%
 
-71.5476110.4%
 
-8430406.6%
 
-7215063.3%
 
-79.6833311302.5%
 
-76.716676801.5%
 
-76.183335391.2%
 
-84.216672630.6%
 
-86.366672260.5%
 
-86.716672170.5%
 
-85.666671850.4%
 
-24.851780.4%
 
-85.633331080.2%
 
-72.95488740.2%
 
-72.77889690.2%
 
-72.98389670.1%
 
58.58333640.1%
 
-72.775570.1%
 
-72.77833520.1%
 
-72.99889410.1%
 
-72.77917400.1%
 
34.08333400.1%
 
-72.7825390.1%
 
-72.983889370.1%
 
29.91667350.1%
 
Other values (12713)1852540.5%
 
(Missing)731516.0%
 
ValueCountFrequency (%) 
-87.366674< 0.1%
 
-87.033333< 0.1%
 
-86.933333< 0.1%
 
-86.716672170.5%
 
-86.5666717< 0.1%
 
-86.544881< 0.1%
 
-86.53791< 0.1%
 
-86.537341< 0.1%
 
-86.537251< 0.1%
 
-86.530351< 0.1%
 
ValueCountFrequency (%) 
81.166671< 0.1%
 
76.533331< 0.1%
 
76.133331< 0.1%
 
72.883331< 0.1%
 
72.683331< 0.1%
 
70.733331< 0.1%
 
701< 0.1%
 
69.11< 0.1%
 
681< 0.1%
 
67.883331< 0.1%
 

reclong
Real number (ℝ)

MISSING
ZEROS

Distinct14640
Distinct (%)38.1%
Missing7315
Missing (%)16.0%
Infinite0
Infinite (%)0.0%
Mean61.05259359
Minimum-165.43333
Maximum354.47333
Zeros6214
Zeros (%)13.6%
Memory size357.4 KiB
2020-10-25T20:17:40.522284image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-165.43333
5-th percentile-90.427
Q10
median35.66667
Q3157.16667
95-th percentile168
Maximum354.47333
Range519.90666
Interquartile range (IQR)157.16667

Descriptive statistics

Standard deviation80.65525774
Coefficient of variation (CV)1.321078319
Kurtosis-0.7313935567
Mean61.05259359
Median Absolute Deviation (MAD)39.53972
Skewness-0.1743813291
Sum2345091.172
Variance6505.2706
MonotocityNot monotonic
2020-10-25T20:17:40.731965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0621413.6%
 
35.66667498510.9%
 
16830406.6%
 
2615063.3%
 
159.756571.4%
 
159.666676371.4%
 
157.166675421.2%
 
155.754731.0%
 
160.52630.6%
 
-702280.5%
 
-141.52170.5%
 
1751850.4%
 
-70.533331780.4%
 
-68.71050.2%
 
160.47328740.2%
 
13.43333640.1%
 
159.33333440.1%
 
75.24639420.1%
 
75.31361420.1%
 
-103.5350.1%
 
157340.1%
 
75.18722330.1%
 
-5.58333330.1%
 
75.2320.1%
 
155.5320.1%
 
Other values (14615)1871640.9%
 
(Missing)731516.0%
 
ValueCountFrequency (%) 
-165.433339< 0.1%
 
-165.1166717< 0.1%
 
-163.166671< 0.1%
 
-162.551< 0.1%
 
-157.866671< 0.1%
 
-157.783331< 0.1%
 
-149.54< 0.1%
 
-148.552< 0.1%
 
-1483< 0.1%
 
-146.266671< 0.1%
 
ValueCountFrequency (%) 
354.473331< 0.1%
 
178.21< 0.1%
 
178.083331< 0.1%
 
175.730281< 0.1%
 
175.133331< 0.1%
 
1751850.4%
 
174.500431< 0.1%
 
174.41< 0.1%
 
172.71< 0.1%
 
172.61< 0.1%
 

GeoLocation
Categorical

HIGH CARDINALITY
MISSING

Distinct17100
Distinct (%)44.5%
Missing7315
Missing (%)16.0%
Memory size357.4 KiB
(0.0, 0.0)
6214 
(-71.5, 35.66667)
4761 
(-84.0, 168.0)
3040 
(-72.0, 26.0)
 
1505
(-79.68333, 159.75)
 
657
Other values (17095)
22234 
ValueCountFrequency (%) 
(0.0, 0.0)621413.6%
 
(-71.5, 35.66667)476110.4%
 
(-84.0, 168.0)30406.6%
 
(-72.0, 26.0)15053.3%
 
(-79.68333, 159.75)6571.4%
 
(-76.71667, 159.66667)6371.4%
 
(-76.18333, 157.16667)5391.2%
 
(-79.68333, 155.75)4731.0%
 
(-84.21667, 160.5)2630.6%
 
(-86.36667, -70.0)2260.5%
 
(0.0, 35.66667)2230.5%
 
(-86.71667, -141.5)2170.5%
 
(-85.66667, 175.0)1850.4%
 
(-24.85, -70.53333)1780.4%
 
(-85.63333, -68.7)1050.2%
 
(-72.95488, 160.47328)740.2%
 
(58.58333, 13.43333)640.1%
 
(-76.71667, 159.33333)420.1%
 
(-72.77889, 75.31361)390.1%
 
(-72.98389, 75.24639)380.1%
 
(-83.25, 157.0)340.1%
 
(29.91667, -5.58333)330.1%
 
(-72.99889, 75.18722)320.1%
 
(-82.5, 155.5)320.1%
 
(-25.23333, -69.71667)320.1%
 
Other values (17075)1876841.0%
 
(Missing)731516.0%
 
2020-10-25T20:17:41.017141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique16363 ?
Unique (%)42.6%
2020-10-25T20:17:41.231336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length24
Median length17
Mean length15.01640205
Min length3

Overview of Unicode Properties

Unique unicode characters18
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.7682211.2%
 
6675609.8%
 
7524997.6%
 
0490337.1%
 
3447716.5%
 
1444766.5%
 
5427576.2%
 
(384115.6%
 
,384115.6%
 
384115.6%
 
)384115.6%
 
8326804.8%
 
2299234.4%
 
-274734.0%
 
4236463.4%
 
9194112.8%
 
n146302.1%
 
a73151.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number40675659.2%
 
Other Punctuation11523316.8%
 
Open Punctuation384115.6%
 
Space Separator384115.6%
 
Close Punctuation384115.6%
 
Dash Punctuation274734.0%
 
Lowercase Letter219453.2%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(38411100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
66756016.6%
 
75249912.9%
 
04903312.1%
 
34477111.0%
 
14447610.9%
 
54275710.5%
 
8326808.0%
 
2299237.4%
 
4236465.8%
 
9194114.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.7682266.7%
 
,3841133.3%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
38411100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)38411100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-27473100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1463066.7%
 
a731533.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common66469596.8%
 
Latin219453.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
.7682211.6%
 
66756010.2%
 
7524997.9%
 
0490337.4%
 
3447716.7%
 
1444766.7%
 
5427576.4%
 
(384115.8%
 
,384115.8%
 
384115.8%
 
)384115.8%
 
8326804.9%
 
2299234.5%
 
-274734.1%
 
4236463.6%
 
9194112.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1463066.7%
 
a731533.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII686640100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.7682211.2%
 
6675609.8%
 
7524997.6%
 
0490337.1%
 
3447716.5%
 
1444766.5%
 
5427576.2%
 
(384115.6%
 
,384115.6%
 
384115.6%
 
)384115.6%
 
8326804.8%
 
2299234.4%
 
-274734.0%
 
4236463.4%
 
9194112.8%
 
n146302.1%
 
a73151.1%
 

source
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size357.4 KiB
NASA
45726 
ValueCountFrequency (%) 
NASA45726100.0%
 
2020-10-25T20:17:41.403272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-25T20:17:41.521318image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-25T20:17:41.615430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
A9145250.0%
 
N4572625.0%
 
S4572625.0%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter182904100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A9145250.0%
 
N4572625.0%
 
S4572625.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin182904100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A9145250.0%
 
N4572625.0%
 
S4572625.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII182904100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
A9145250.0%
 
N4572625.0%
 
S4572625.0%
 

boolean
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.8 KiB
True
22934 
False
22792 
ValueCountFrequency (%) 
True2293450.2%
 
False2279249.8%
 
2020-10-25T20:17:41.712648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mixed
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size357.4 KiB
A
22889 
1
22837 
ValueCountFrequency (%) 
A2288950.1%
 
12283749.9%
 
2020-10-25T20:17:41.823352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-25T20:17:41.935588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-25T20:17:42.038857image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Overview of Unicode Properties

Unique unicode characters2
Unique unicode categories2 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
A2288950.1%
 
12283749.9%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter2288950.1%
 
Decimal Number2283749.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
122837100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A22889100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin2288950.1%
 
Common2283749.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
122837100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A22889100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII45726100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
A2288950.1%
 
12283749.9%
 

reclat_city
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct38401
Distinct (%)> 99.9%
Missing7315
Missing (%)16.0%
Infinite0
Infinite (%)0.0%
Mean-39.15354218
Minimum-104.3171665
Maximum77.74901083
Zeros0
Zeros (%)0.0%
Memory size357.4 KiB
2020-10-25T20:17:42.229436image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-104.3171665
5-th percentile-87.87105763
Q1-78.40775202
median-68.97529272
Q34.788644923
95-th percentile35.42980961
Maximum77.74901083
Range182.0661773
Interquartile range (IQR)83.19639695

Descriptive statistics

Standard deviation46.68568721
Coefficient of variation (CV)-1.192374549
Kurtosis-1.446385025
Mean-39.15354218
Median Absolute Deviation (MAD)17.25584321
Skewness0.4816035823
Sum-1503926.709
Variance2179.55339
MonotocityNot monotonic
2020-10-25T20:17:42.581727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/