Latest Updates

Version 0.2.0 includes the first public beta API access using the get_event() function, offering users easy access to the CoronaNet Event Dataset as R data frames.

Installation

You can install the development version of CoronaNetR as follows:

devtools::install_github("CoronaNetDataScience/CoronaNetR")

Event Data: get_event()

Access CoronaNet’s Event Dataset. The function allows you to filter by policy type (type), policy subtype (type_sub_cat), and date (from and to).

head(get_event(countries = "All", type = "All", type_sub_cat = "All", from = "2019-12-31", to = "2020-01-10"))

## Rows: 64 Columns: 28
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (23): record_id, policy_id, entry_type, update_type, update_level, upda...
## lgl   (2): target_intl_org, target_other
## date  (3): date_announced, date_start, date_end
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 6 × 28
##   record_id        polic…¹ entry…² updat…³ updat…⁴ updat…⁵ date_ann…⁶ date_start
##   <chr>            <chr>   <chr>   <chr>   <chr>   <chr>   <date>     <date>    
## 1 R_3n788do2QRzmN… 8472080 new_en… <NA>    <NA>    <NA>    2020-03-14 2020-01-03
## 2 R_1Leg47dGNydFw… 8856106 new_en… <NA>    <NA>    <NA>    2020-01-06 2020-01-06
## 3 R_3kidvyxTvdHn0… 2967891 new_en… <NA>    <NA>    <NA>    NA         2019-12-31
## 4 R_1GJJ7V1shrFkv… 2971618 new_en… <NA>    <NA>    <NA>    2020-01-01 2020-01-01
## 5 R_2AMF4PcSVHjxT… 1884124 new_en… <NA>    <NA>    <NA>    2020-02-25 2020-01-01
## 6 R_2CdDjoSFr0msV… 8936839 new_en… <NA>    <NA>    <NA>    2019-12-31 2019-12-31
## # … with 20 more variables: date_end <date>, date_end_spec <chr>,
## #   country <chr>, init_country_level <chr>, province <chr>,
## #   target_init_same <chr>, target_country <chr>, target_province <chr>,
## #   target_city <chr>, target_intl_org <lgl>, target_other <lgl>,
## #   target_who_what <chr>, target_who_gen <chr>, target_direction <chr>,
## #   compliance <chr>, enforcer <chr>, city <chr>, type <chr>,
## #   type_sub_cat <chr>, description <chr>, and abbreviated variable names …

There are a lot of records that do not yet have end dates, so these are included by default. To exclude them, set the include_no_end_date argument to FALSE.

By default a set of columns is included that can identify each record, but only includes the policy target, type and description. To change this default, you can pass a character vector to the default_columns argument. However, it is better to leave that argument unchanged and add any additional desired columns as a character vector to the additional_columns argument. A full list of columns is available in our codebook.

Policy Intensity Indexes: get_policy_scores

You can download our six different policy intensity indexes, which are covered in this paper, and aggregate our data into daily country-level policy intensity scores using the get_policy_scores function:

head(get_policy_scores(from="2020-01-01",
                       to="2020-01-10"))

## Rows: 11010 Columns: 7
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (2): country, modtype
## dbl  (4): med_est, high_est, low_est, sd_est
## date (1): date_policy
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 6 × 7
##   country     modtype               date_policy  med_est high_est low_est sd_est
##   <chr>       <chr>                 <date>         <dbl>    <dbl>   <dbl>  <dbl>
## 1 Afghanistan Business Restrictions 2020-01-01  -0.186    -0.149  -0.213  0.0194
## 2 Afghanistan Health Monitoring     2020-01-01   0.00669   0.124  -0.0364 0.0451
## 3 Afghanistan Health Resources      2020-01-01  -0.0384    0.0580 -0.0918 0.0428
## 4 Afghanistan Mask Policies         2020-01-01   0.0250    0.0836 -0.0778 0.0450
## 5 Afghanistan School Restrictions   2020-01-01  -0.00681   0.0742 -0.0649 0.0426
## 6 Afghanistan Social Distancing     2020-01-01  -0.172    -0.122  -0.217  0.0292

These scores are estimated with measurement error, both the standard deviation of the uncertainty of the scores and a high/low uncertainty interval. This information is useful for checking results for robustness to coding and other kinds of errors in the scores. These indexes are periodically updated as we add more records to our CoronaNet database. The indexes currently run from January 1st, 2020 to April 29th, 2021 for over 180 countries.

Policy Type (type) and Subtype Options (type_sub_cat)

The CoronaNet dataset has 20 main policy types and 258 policy sub-types (not all sub types are available for all main types). By default, the get_events() function will select all policy types and sub-types, but more specific criteria can be set by passing a character vector of relevant types/sub-types to the type and type_sub_cat arguments. To see a list of available policy types, please see our codebook.

Date

You can select a subset of the records using the from and to arguments (both must be specified) in YYYY-MM-DD format as a character value. These arguments correspond to the coded policy begin and end dates for a given policy record.

Country

You can select a specific country to access records using the country argument. This will also pull sub-national policies for that country. A sub-national record will have a value in either the province or city column of the record.