Overview

Dataset statistics

Number of variables7
Number of observations1376
Missing cells0
Missing cells (%)0.0%
Total size in memory75.4 KiB
Average record size in memory56.1 B

Variable types

Numeric2
Text5

Variable descriptions

carbon_taxamount of carbon tax, in USD$/tCO2
modelIAM which produced the production pathways
scenarioname of the scenario
scenario_geographyregional geography of a scenario
unitunit of production
variablevariable of the carbon price
yearyear

Alerts

variable has constant value ""Constant
unit has constant value ""Constant
carbon_tax has 388 (28.2%) zerosZeros

Reproduction

Analysis started2024-04-15 12:05:13.491263
Analysis finished2024-04-15 12:05:13.540258
Duration0.05 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

year
Real number (ℝ)

year

Distinct86
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2057.5
Minimum2015
Maximum2100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-15T14:05:13.619041image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2019
Q12036
median2057.5
Q32079
95-th percentile2096
Maximum2100
Range85
Interquartile range (IQR)43

Descriptive statistics

Standard deviation24.83340858
Coefficient of variation (CV)0.0120697004
Kurtosis-1.200324454
Mean2057.5
Median Absolute Deviation (MAD)21.5
Skewness0
Sum2831120
Variance616.6981818
MonotonicityNot monotonic
2024-04-15T14:05:13.772162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2015 16
 
1.2%
2069 16
 
1.2%
2077 16
 
1.2%
2076 16
 
1.2%
2075 16
 
1.2%
2074 16
 
1.2%
2073 16
 
1.2%
2072 16
 
1.2%
2071 16
 
1.2%
2070 16
 
1.2%
Other values (76) 1216
88.4%
ValueCountFrequency (%)
2015 16
1.2%
2016 16
1.2%
2017 16
1.2%
2018 16
1.2%
2019 16
1.2%
ValueCountFrequency (%)
2100 16
1.2%
2099 16
1.2%
2098 16
1.2%
2097 16
1.2%
2096 16
1.2%

model
Text

IAM which produced the production pathways

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
2024-04-15T14:05:13.936138image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length36
Median length14
Mean length16.1875
Min length13

Characters and Unicode

Total characters22274
Distinct characters30
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 rowGCAM 5.3+ NGFS
2nd rowGCAM 5.3+ NGFS
3rd rowGCAM 5.3+ NGFS
4th rowGCAM 5.3+ NGFS
5th rowGCAM 5.3+ NGFS
ValueCountFrequency (%)
gcam 1032
30.0%
5.3 1032
30.0%
ngfs 1032
30.0%
flat_carbon_tax_50 86
 
2.5%
increasing_carbon_tax_50 86
 
2.5%
independent_increasing_carbon_tax_50 86
 
2.5%
no_carbon_tax 86
 
2.5%
2024-04-15T14:05:14.214260image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 2064
 
9.3%
2064
 
9.3%
5 1290
 
5.8%
N 1032
 
4.6%
C 1032
 
4.6%
n 1032
 
4.6%
S 1032
 
4.6%
F 1032
 
4.6%
+ 1032
 
4.6%
3 1032
 
4.6%
Other values (20) 9632
43.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 22274
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 2064
 
9.3%
2064
 
9.3%
5 1290
 
5.8%
N 1032
 
4.6%
C 1032
 
4.6%
n 1032
 
4.6%
S 1032
 
4.6%
F 1032
 
4.6%
+ 1032
 
4.6%
3 1032
 
4.6%
Other values (20) 9632
43.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 22274
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 2064
 
9.3%
2064
 
9.3%
5 1290
 
5.8%
N 1032
 
4.6%
C 1032
 
4.6%
n 1032
 
4.6%
S 1032
 
4.6%
F 1032
 
4.6%
+ 1032
 
4.6%
3 1032
 
4.6%
Other values (20) 9632
43.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 22274
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 2064
 
9.3%
2064
 
9.3%
5 1290
 
5.8%
N 1032
 
4.6%
C 1032
 
4.6%
n 1032
 
4.6%
S 1032
 
4.6%
F 1032
 
4.6%
+ 1032
 
4.6%
3 1032
 
4.6%
Other values (20) 9632
43.2%

scenario
Text

name of the scenario

Distinct16
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
2024-04-15T14:05:14.419328image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length36
Median length23
Mean length16.9375
Min length3

Characters and Unicode

Total characters23306
Distinct characters33
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 rowB2DS
2nd rowB2DS
3rd rowB2DS
4th rowB2DS
5th rowB2DS
ValueCountFrequency (%)
b2ds 86
 
5.6%
b2ds_indonesia 86
 
5.6%
independent_increasing_carbon_tax_50 86
 
5.6%
increasing_carbon_tax_50 86
 
5.6%
flat_carbon_tax_50 86
 
5.6%
nz2050_indonesia_market_assumption 86
 
5.6%
nz2050_indonesia 86
 
5.6%
nz2050 86
 
5.6%
ndc_indonesia_moderate 86
 
5.6%
ndc_indonesia_market_assumption 86
 
5.6%
Other values (8) 688
44.4%
2024-04-15T14:05:14.771718image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2494
 
10.7%
a 2064
 
8.9%
_ 1978
 
8.5%
e 1634
 
7.0%
i 1462
 
6.3%
o 1376
 
5.9%
s 1204
 
5.2%
t 1204
 
5.2%
r 1032
 
4.4%
0 946
 
4.1%
Other values (23) 7912
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23306
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 2494
 
10.7%
a 2064
 
8.9%
_ 1978
 
8.5%
e 1634
 
7.0%
i 1462
 
6.3%
o 1376
 
5.9%
s 1204
 
5.2%
t 1204
 
5.2%
r 1032
 
4.4%
0 946
 
4.1%
Other values (23) 7912
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23306
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 2494
 
10.7%
a 2064
 
8.9%
_ 1978
 
8.5%
e 1634
 
7.0%
i 1462
 
6.3%
o 1376
 
5.9%
s 1204
 
5.2%
t 1204
 
5.2%
r 1032
 
4.4%
0 946
 
4.1%
Other values (23) 7912
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23306
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 2494
 
10.7%
a 2064
 
8.9%
_ 1978
 
8.5%
e 1634
 
7.0%
i 1462
 
6.3%
o 1376
 
5.9%
s 1204
 
5.2%
t 1204
 
5.2%
r 1032
 
4.4%
0 946
 
4.1%
Other values (23) 7912
33.9%

scenario_geography
Text

regional geography of a scenario

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
2024-04-15T14:05:14.920493image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length9
Median length7.5
Mean length7.5
Min length6

Characters and Unicode

Total characters10320
Distinct characters11
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 rowGlobal
2nd rowGlobal
3rd rowGlobal
4th rowGlobal
5th rowGlobal
ValueCountFrequency (%)
global 688
50.0%
indonesia 688
50.0%
2024-04-15T14:05:15.260657image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1376
13.3%
o 1376
13.3%
a 1376
13.3%
n 1376
13.3%
G 688
6.7%
b 688
6.7%
I 688
6.7%
d 688
6.7%
e 688
6.7%
s 688
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10320
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1376
13.3%
o 1376
13.3%
a 1376
13.3%
n 1376
13.3%
G 688
6.7%
b 688
6.7%
I 688
6.7%
d 688
6.7%
e 688
6.7%
s 688
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10320
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1376
13.3%
o 1376
13.3%
a 1376
13.3%
n 1376
13.3%
G 688
6.7%
b 688
6.7%
I 688
6.7%
d 688
6.7%
e 688
6.7%
s 688
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10320
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1376
13.3%
o 1376
13.3%
a 1376
13.3%
n 1376
13.3%
G 688
6.7%
b 688
6.7%
I 688
6.7%
d 688
6.7%
e 688
6.7%
s 688
6.7%

variable
Text

CONSTANT 

variable of the carbon price

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
2024-04-15T14:05:15.404913image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters16512
Distinct characters11
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 rowPrice|Carbon
2nd rowPrice|Carbon
3rd rowPrice|Carbon
4th rowPrice|Carbon
5th rowPrice|Carbon
ValueCountFrequency (%)
price|carbon 1376
100.0%
2024-04-15T14:05:15.664023image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 2752
16.7%
P 1376
8.3%
i 1376
8.3%
c 1376
8.3%
e 1376
8.3%
| 1376
8.3%
C 1376
8.3%
a 1376
8.3%
b 1376
8.3%
o 1376
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16512
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 2752
16.7%
P 1376
8.3%
i 1376
8.3%
c 1376
8.3%
e 1376
8.3%
| 1376
8.3%
C 1376
8.3%
a 1376
8.3%
b 1376
8.3%
o 1376
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16512
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 2752
16.7%
P 1376
8.3%
i 1376
8.3%
c 1376
8.3%
e 1376
8.3%
| 1376
8.3%
C 1376
8.3%
a 1376
8.3%
b 1376
8.3%
o 1376
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16512
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 2752
16.7%
P 1376
8.3%
i 1376
8.3%
c 1376
8.3%
e 1376
8.3%
| 1376
8.3%
C 1376
8.3%
a 1376
8.3%
b 1376
8.3%
o 1376
8.3%

unit
Text

CONSTANT 

unit of production

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.9 KiB
2024-04-15T14:05:15.804501image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters17888
Distinct characters11
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 rowUS$2010/t CO2
2nd rowUS$2010/t CO2
3rd rowUS$2010/t CO2
4th rowUS$2010/t CO2
5th rowUS$2010/t CO2
ValueCountFrequency (%)
us$2010/t 1376
50.0%
co2 1376
50.0%
2024-04-15T14:05:16.067767image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2752
15.4%
0 2752
15.4%
U 1376
7.7%
S 1376
7.7%
$ 1376
7.7%
1 1376
7.7%
/ 1376
7.7%
t 1376
7.7%
1376
7.7%
C 1376
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17888
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2752
15.4%
0 2752
15.4%
U 1376
7.7%
S 1376
7.7%
$ 1376
7.7%
1 1376
7.7%
/ 1376
7.7%
t 1376
7.7%
1376
7.7%
C 1376
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17888
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2752
15.4%
0 2752
15.4%
U 1376
7.7%
S 1376
7.7%
$ 1376
7.7%
1 1376
7.7%
/ 1376
7.7%
t 1376
7.7%
1376
7.7%
C 1376
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17888
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2752
15.4%
0 2752
15.4%
U 1376
7.7%
S 1376
7.7%
$ 1376
7.7%
1 1376
7.7%
/ 1376
7.7%
t 1376
7.7%
1376
7.7%
C 1376
7.7%

carbon_tax
Real number (ℝ)

ZEROS 

amount of carbon tax, in USD$/tCO2

Distinct638
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean392.5552411
Minimum0
Maximum2529.024082
Zeros388
Zeros (%)28.2%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-15T14:05:16.214239image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median64.35301103
Q3619.6314007
95-th percentile1888.263637
Maximum2529.024082
Range2529.024082
Interquartile range (IQR)619.6314007

Descriptive statistics

Standard deviation614.8359975
Coefficient of variation (CV)1.566240705
Kurtosis2.816990522
Mean392.5552411
Median Absolute Deviation (MAD)64.35301103
Skewness1.864245792
Sum540156.0118
Variance378023.3038
MonotonicityNot monotonic
2024-04-15T14:05:16.369295image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 388
28.2%
50 153
 
11.1%
1436.256733 2
 
0.1%
975.2010701 2
 
0.1%
948.8641512 2
 
0.1%
935.6956918 2
 
0.1%
928.948572 2
 
0.1%
922.2014523 2
 
0.1%
908.7072128 2
 
0.1%
901.9600931 2
 
0.1%
Other values (628) 819
59.5%
ValueCountFrequency (%)
0 388
28.2%
2 1
 
0.1%
2.8 1
 
0.1%
3.6 1
 
0.1%
4.4 1
 
0.1%
ValueCountFrequency (%)
2529.024082 1
0.1%
2519.618434 1
0.1%
2516.447326 1
0.1%
2515.939469 1
0.1%
2510.212785 1
0.1%