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5. Data
π We maintain a data repository updated daily that contains the data displayed on the site in a standardized, TIDY format. That means that every data point is a row (line) and every data feature is a column. The first column is called the index, and it is the typcially the column, based on which each of the data points gets a unique identifier. pandas
automatically assigns this column to its index upon load, but the standard CSV
format does not. Therefore, sometimes (especially for the case of time series data) the index column of datasets is a date. This makes pandas
treat the data series as time series.
index | feature1 | feature2 |
---|---|---|
data1.index | data1.feature1 | data1.feature2 |
data2.index | data2.feature1 | data2.feature2 |
... | ||
data42.index | data42.feature1 | data42.feature2 |
... |
During the data transformation and normalization process, the objective is to minimize the number of data columns. This means that this format ...
Country | 2019 | 2020 | 2021 |
---|---|---|---|
Austria | 42 | 13 | 69 |
Belgium | 75 | 12 | 77 |
... should be converted to this:
Country | Year | Value |
---|---|---|
Austria | 2019 | 42 |
Austria | 2020 | 13 |
Austria | 2021 | 69 |
Belgium | 2019 | 75 |
Belgium | 2020 | 12 |
Belgium | 2021 | 77 |
This operation is typically called a stack
in pandas
and a pivot
in Excel/PowerBI.
Then, the following hold true:
-
Every row (line) contains a unique data point
-
Each data point is
n
-dimensional (caution! see below), wheren
equals the number of columns, i.e. each data points hasn
features. -
The dataset has
m
elements, wherem
equals the number of rows -
Likewise, the dataset can be represented as an
n
bym
matrix -
Columns headers are called features. Sometimes they are also called headers, (data) attributes or even (data) properties. The latter comes from the fact that when the data is not in a table format, it is often in a standardized
JSON
format, like this:[ {"index":data1.index,"feature1":data1.feature1,"feature2":data1.feature2}, {"index":data2.index,"feature1":data2.feature1,"feature2":data2.feature2}, ..., {"index":data42.index,"feature1":data42.feature1,"feature2":data42.feature2}, ... ]
- In
JSON/JavaScript
lingo, this would be called aJavaScript
Object Array, whereindex
,feature1
andfeature2
are called properties. - In
python
, this would be called a list of dictionaries, whereindex
,feature1
andfeature2
are called keys. - In both cases,
data1.index, data1.feature1, ...
are called values. - Likewise, in
JSON/JavaScript
the dataset can be represented as Array of lengthm
, with each element being an Object containingn
property-value pairs. - Likewise, in
python
the dataset can be represented as list of lengthm
, with each element being an dictionary containingn
key-value pairs.
- In
-
The type of the features can be field or tag β¬ this is InfluxDB lingo. You might see them referred to as fact and dimension tables.
- A fact is a measurable data value for the respective data point in each row. You might simply refer to this as a (quantitative or continuous) value.
- A dimension is a descriptive tag for the respective data point in each row. You might refer to this as a tag, a label or a nominal value.
- Sometimes the fact columns of the data table (fact table) is simply called data, and the dimension columns (dimension table) is called metadata.
- Somewhat incorrectly and confusingly, dimension is also used colloquially to refer to a feature in general. This comes from the fact that the size of the data
=
nr of columnsx
nr of rows. This could allude to the fact that the data isn
dimensional, wheren
equals the number of columns, i.e. the number of data features. - To avoid confusion, we prefer to use the column/feature β‘ field and tag nomenclature.
-
Time series datasets have dates in the
yyyy-mm-dd
format as their index and are sorted in increasing order. -
Data series datasets have an increasing numerical range index starting from
0
. -
*_mirror
type datasets are local mirrors of external datasets and typically retain the format of their respective original sources. - Column names are typically self-explanatory, unless otherwise noted in the Comments column.
This the major situation update dataset, containing daily COVID-19 case, testing and vaccination updates. Contains both Cumulative values, as well as Daily rates.
- π Updated daily at π 14:00 by @roeimbot
- π Data sources:
- Θtiri Oficiale/DateLaZi for case data
- data.gov.ro for vaccination data
- graphs.ro for testing data | API
Column name | Column type | Data type | Data subtype | Comments |
---|---|---|---|---|
date |
index | datetime | date | yyyy-mm-dd |
cases |
field | quantitative | integer | Cumulative |
heals |
field | quantitative | integer | Cumulative |
deaths |
field | quantitative | integer | Cumulative |
total_administered |
field | quantitative | integer | Cumulative |
total_administered_pfizer |
field | quantitative | integer | Cumulative |
total_immunized |
field | quantitative | integer | Cumulative |
total_immunized_pfizer |
field | quantitative | integer | Cumulative |
total_administered_moderna |
field | quantitative | integer | Cumulative |
total_immunized_moderna |
field | quantitative | integer | Cumulative |
total_administered_astra_zeneca |
field | quantitative | integer | Cumulative |
total_immunized_astra_zeneca |
field | quantitative | integer | Cumulative |
active |
field | quantitative | integer | Daily rate |
case |
field | quantitative | integer | Daily rate |
heal |
field | quantitative | integer | Daily rate |
death |
field | quantitative | integer | Daily rate |
administered |
field | quantitative | integer | Daily rate |
administered_pfizer |
field | quantitative | integer | Daily rate |
immunized |
field | quantitative | integer | Daily rate |
immunized_pfizer |
field | quantitative | integer | Daily rate |
administered_moderna |
field | quantitative | integer | Daily rate |
immunized_moderna |
field | quantitative | integer | Daily rate |
administered_astra_zeneca |
field | quantitative | integer | Daily rate |
immunized_astra_zeneca |
field | quantitative | integer | Daily rate |
tests |
field | quantitative | integer | Cumulative |
test |
field | quantitative | integer | Daily rate |
case14 |
field | quantitative | integer | Rolling cumulative |
This the major county-level dataset, containing daily COVID-19 case updates on a county level. Contains both Cumulative as well as 14-day Rolling cumulative values, both in absolute and per capita forms.
- π Updated daily at π 14:00 by @roeimbot
- π Data sources:
- Θtiri Oficiale/DateLaZi for case data
Column name | Column type | Data type | Data subtype | Comments |
---|---|---|---|---|
date |
field | datetime | date | yyyy-mm-dd |
cases |
field | quantitative | integer | Cumulative |
case_cap |
field | quantitative | float | Cumulative - per capita |
pop |
field | quantitative | integer | Constant - Population |
county |
tag | nominal | county | in Romanian |
iso |
tag | nominal | 2-letter label | County code in Romanian |
case_14 |
field | quantitative | integer | Rolling cumulative |
case_14_cap |
field | quantitative | float | Rolling cumulative - per capita |
id |
tag | ordinal | integer | County code in topojson
|
lang |
tag | nominal | 2-letter label | Constant = "RO"
|
This the major UAT-level (local administrative unit) dataset, driving the incidence map. It contains infection incidence rates (new case totals of last 14 days/1000 people - with 17 to 3 days before the date displayed) per UAT.
-
π Updated daily (for the previous day) at π 10:02 by @roeimbot
-
π Data sources:
- data.gov.ro for UAT-level infection incidence rates
Column name | Column type | Data type | Data subtype | Comments |
---|---|---|---|---|
date |
field | datetime | date | yyyy-mm-dd |
judet |
tag | nominal | county | in Romanian, source |
uat |
tag | nominal | local administrative unit | in Romanian, source |
siruta |
tag | nominal | integer | SIRUTA codes |
judet_norm |
tag | nominal | county | in Romanian, normalized |
uat_norm |
tag | nominal | local administrative unit | in Romanian, normalized |
incidence |
field | quantitative | float | Incidence rate / 1000 people |
Country level, cumulative cases, recovered and deaths dataset
- π Mirrored dataset
- π Updated every few days, manually
- π Data sources:
- John Hopkins CSSE for country-level data | API cases, recovered, deaths
The data is in non-standard format. The index is a datetime in the yyyy-mm-dd
format, but the data values are in columns and not rows. Each country is a column, noted by its 2-digit ISO code, in lowercase.
- d
- d
- d
- d
- d
- d
Date-tagged list of economic, financial and social measures introduced by the Romanian Government during the pandemic
-
π Updated every few days, manually
-
π Own dataset, based on Θtiri Oficiale
Column name | Column type | Data type | Data subtype | Comments |
---|---|---|---|---|
date |
field | datetime | date | yyyy-mm-dd |
desc |
tag | nominal | date | Summary |
link |
tag | nominal | url | Announcement link |
lang |
tag | nominal | 2-letter label | Measure language |
desc2 |
tag | nominal | label | Announcement type |
desc3 |
tag | nominal | label | Measure type |
- d
- d
- d
- d
- d
- d
- d
- d
- d
- d
π·π΄πΉππ COVID-19 - Romanian Economic Impact Monitor https://econ.ubbcluj.ro/coronavirus