Using Mosqlient from R¶
This is an R notebook that demonstrates how to use the Mosqlient package to interact with the Mosqlimate platform and API.
Installation¶
Make sure you have the R kernel installed in your Jupyter notebook. If not, you can install it by running the following command in your R terminal:
> install.packages("IRkernel")
> IRkernel::installspec()
In you local computer make sure you have Python installed.
Install the reticulate package in R:
install.packages('pak')
library(pak)
pak::pak("rstudio/reticulate")
Now you are ready to install the mosqlient package within R.
To get started, you will need to use the package reticulate to load the mosqlient python package:
In [1]:
Copied!
library(reticulate)
library(reticulate)
Then, you can install mosqlient from within R like this:
In [ ]:
Copied!
py_install("mosqlient")
py_install("mosqlient")
Using virtual environment 'r_mosq' ...
+ /Users/eduardoaraujo/.virtualenvs/r_mosq/bin/python -m pip install --upgrade --no-user 'mosqlient==1.9.2'
Once you are sure to have mosqlient installed and the virtualenv installed, using one of the options above, you ca go ahead and "import" the mosqlient package.
In [4]:
Copied!
mosq <- import("mosqlient")
mosq <- import("mosqlient")
In [5]:
Copied!
# checking it works. Showing the current version
mosq$version
# checking it works. Showing the current version
mosq$version
'1.9.2'
If your version is below 1.9.2, start by creating a virtual environment and verifying the Python version in use. Make sure it falls between versions 3.10 and 3.12. If necessary, you can specify the path to your Python installation using the python parameter:
virtualenv_create("r_mosq", python = "/opt/homebrew/opt/python@3.12")`
use_virtualenv("r_mosq", required = TRUE)
py_config()
Load your API_KEY. If it's stored in a .env file, you can use the dotenv package to load it. Be sure to specify the path to the .env file using the file parameter.
In [6]:
Copied!
install.packages('dotenv')
install.packages('dotenv')
The downloaded binary packages are in /var/folders/ch/kxpr39wx44v97968yr_4hmch0000gn/T//RtmpVC7wWR/downloaded_packages
In [ ]:
Copied!
library(dotenv)
# Load .env file (must be in working directory or specify the path)
load_dot_env(file = file.path(Sys.getenv("GITHUB_WORKSPACE"), ".env"))
# Get the API key
api_key <- Sys.getenv("API_KEY")
library(dotenv)
# Load .env file (must be in working directory or specify the path)
load_dot_env(file = file.path(Sys.getenv("GITHUB_WORKSPACE"), ".env"))
# Get the API key
api_key <- Sys.getenv("API_KEY")
Warning message: “package ‘dotenv’ was built under R version 4.3.3”
Using Mosqlient¶
let's start by checking a list of the models registered in the platform
In [8]:
Copied!
model_list <- mosq$get_all_models(api_key=api_key)
model_list
model_list <- mosq$get_all_models(api_key=api_key)
model_list
[[1]] 2025 sprint test - Prophet DF [[2]] 2025 sprint test - Prophet [[3]] 2025 sprint test [[4]] Example of Univariate neural prophet model [[5]] My Nowcasting Model [[6]] infodengue_sprint_24_25_hybrid_CNN_LSTM_ensemble_model [[7]] Model 2 - Weekly and yearly (rw1) components [[8]] Model 1 - Weekly and yearly (iid) components [[9]] BB-M [[10]] Temp-SPI Interaction Model [[11]] LSTM model with PCA and vaiance threshold [[12]] Prophet model with PCA and vaiance threshold [[13]] LSTM model for Infodengue Sprint [[14]] Univariate neural prophet model [[15]] Deep learning model using BI-LSTM Layers [[16]] Random Forest model with uncertainty computed with conformal prediction [[17]] Baseline weekly model [[18]] autoarima [[19]] autoarima [[20]] test model [[21]] LSTM model
Fetching data from the Mosqlimate datastore¶
We can use the Mosqlient library to fetch data from Mosqlimate. Let's start fetching some data from the infodengue project.
In [9]:
Copied!
data <- mosq$get_infodengue(api_key = api_key, disease='dengue', start_date='2023-12-01',end_date='2023-12-31', uf='RJ')
data
data <- mosq$get_infodengue(api_key = api_key, disease='dengue', start_date='2023-12-01',end_date='2023-12-31', uf='RJ')
data
| data_iniSE | SE | casos_est | casos_est_min | casos_est_max | casos | municipio_geocodigo | p_rt1 | p_inc100k | Localidade_id | ⋯ | nivel_inc | umidmed | umidmin | tempmed | tempmax | casprov | casprov_est | casprov_est_min | casprov_est_max | casconf |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ⋯ | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | <chr> | <chr> |
| 2023-12-31 | 202401 | 11 | 11 | 11 | 11 | 3301207 | 0.9261000 | 64.143684 | 0 | ⋯ | 1 | 86.31443 | 74.81649 | 22.08231 | 24.50814 | 5 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 5 | 5 | 5 | 5 | 3305752 | 0.9957709 | 16.041580 | 0 | ⋯ | 1 | 83.27701 | 73.67101 | 23.64674 | 25.60710 | 1 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 12 | 12 | 12 | 12 | 3301801 | 0.9804760 | 101.505670 | 0 | ⋯ | 2 | 84.59954 | 72.56147 | 22.40403 | 24.94773 | 3 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 19 | 19 | 19 | 19 | 3301850 | 0.9841978 | 37.691680 | 0 | ⋯ | 2 | 86.38757 | 75.17570 | 23.18124 | 25.59660 | 10 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 13 | 13 | 13 | 13 | 3303005 | 0.9517184 | 48.791473 | 0 | ⋯ | 1 | 85.84879 | 74.12201 | 23.23376 | 25.43500 | 5 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 9 | 9 | 9 | 9 | 3303955 | 0.6903663 | 36.655400 | 0 | ⋯ | 1 | 84.15786 | 72.26394 | 22.64483 | 25.40886 | 4 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 28 | 28 | 28 | 28 | 3304110 | 0.9985263 | 137.423310 | 0 | ⋯ | 2 | 85.58869 | 73.05383 | 21.88330 | 24.87064 | 8 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 30 | 30 | 30 | 30 | 3305505 | 0.9995135 | 33.800910 | 0 | ⋯ | 1 | 82.67047 | 75.28619 | 24.29591 | 25.77090 | 9 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 3 | 3 | 3 | 3 | 3300225 | 0.9421743 | 25.499363 | 0 | ⋯ | 0 | 88.34176 | 77.60486 | 21.04411 | 23.62354 | 3 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 5 | 5 | 5 | 5 | 3304409 | 0.9895125 | 26.962898 | 0 | ⋯ | 0 | 83.70591 | 73.09774 | 22.03871 | 24.56499 | 2 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 243 | 243 | 243 | 243 | 3304524 | 1.0000000 | 162.474430 | 0 | ⋯ | 2 | 85.32911 | 76.09460 | 23.98634 | 25.63654 | 132 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 32 | 32 | 32 | 32 | 3304706 | 0.9999996 | 78.297040 | 0 | ⋯ | 2 | 85.59579 | 73.79844 | 23.45407 | 25.70076 | 19 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 26 | 26 | 26 | 26 | 3305307 | 0.9999860 | 337.355650 | 0 | ⋯ | 2 | 86.75343 | 74.30880 | 22.68927 | 24.97696 | 26 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 3 | 3 | 3 | 3 | 3303203 | 0.9864174 | 1.996260 | 0 | ⋯ | 0 | 79.55936 | 64.87224 | 24.47613 | 27.28331 | 3 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 19 | 19 | 19 | 19 | 3306107 | 0.9997008 | 26.292482 | 0 | ⋯ | 2 | 86.07799 | 73.71303 | 21.39617 | 24.11010 | 5 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 22 | 22 | 22 | 22 | 3300456 | 0.9319806 | 4.924664 | 0 | ⋯ | 2 | 82.61673 | 68.62017 | 24.47834 | 27.22931 | 5 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 203 | 203 | 203 | 203 | 3300100 | 1.0000000 | 112.013596 | 0 | ⋯ | 2 | 85.79797 | 76.52670 | 21.45544 | 23.74159 | 153 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 5 | 5 | 5 | 5 | 3302809 | 0.9596037 | 28.635244 | 0 | ⋯ | 1 | 84.93214 | 73.34896 | 22.50846 | 25.06700 | 1 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 7 | 7 | 7 | 7 | 3300258 | 0.9974380 | 22.558815 | 0 | ⋯ | 1 | 81.65181 | 75.50570 | 24.24280 | 25.36699 | 3 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 45 | 45 | 45 | 45 | 3301306 | 0.9999582 | 98.749176 | 0 | ⋯ | 2 | 86.45163 | 76.59390 | 23.09910 | 24.94353 | 6 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 26 | 26 | 26 | 26 | 3300233 | 0.9999997 | 66.610306 | 0 | ⋯ | 2 | 81.84831 | 75.64057 | 24.49191 | 25.55229 | 24 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 11 | 11 | 11 | 11 | 3303856 | 0.9979631 | 37.427696 | 0 | ⋯ | 2 | 86.53097 | 75.49444 | 21.22587 | 23.63109 | 9 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 18 | 18 | 18 | 18 | 3300308 | 0.9963596 | 19.774788 | 0 | ⋯ | 2 | 84.83489 | 73.25777 | 22.02057 | 24.66976 | 10 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 38 | 38 | 38 | 38 | 3302601 | 0.9996798 | 97.553460 | 0 | ⋯ | 2 | 83.80877 | 74.03489 | 22.49611 | 24.82051 | 14 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 32 | 32 | 32 | 32 | 3300803 | 0.9991648 | 59.383526 | 0 | ⋯ | 2 | 87.86720 | 77.60239 | 22.52993 | 24.84526 | 26 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 3 | 3 | 3 | 3 | 3302304 | 0.9872154 | 44.332790 | 0 | ⋯ | 0 | 85.97001 | 74.97896 | 23.07184 | 25.33293 | 3 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 12 | 12 | 12 | 12 | 3301108 | 0.9436649 | 61.718872 | 0 | ⋯ | 1 | 86.02594 | 74.06677 | 22.33466 | 24.73559 | 12 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 156 | 156 | 156 | 156 | 3303500 | 1.0000000 | 19.044502 | 0 | ⋯ | 2 | 82.55169 | 68.76487 | 23.80997 | 26.53031 | 58 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 6 | 6 | 6 | 6 | 3305554 | 0.9828328 | 7.029136 | 0 | ⋯ | 1 | 83.18103 | 70.21560 | 24.25607 | 26.86407 | 4 | NA | NA | NA | NA |
| 2023-12-31 | 202401 | 101 | 101 | 101 | 101 | 3303906 | 1.0000000 | 33.141050 | 0 | ⋯ | 2 | 87.72831 | 77.22151 | 20.25073 | 22.68356 | 57 | NA | NA | NA | NA |
| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋱ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |
| 2023-12-03 | 202349 | 1 | 1 | 1 | 1 | 3303302 | 0.006431249 | 0.1909621 | 0 | ⋯ | 0 | 77.48269 | 59.89254 | 27.45761 | 31.36540 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3304409 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 83.62517 | 66.92873 | 24.46984 | 28.29846 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3305158 | 0.500000000 | 0.0000000 | 0 | ⋯ | 0 | 81.01003 | 61.66251 | 23.96716 | 28.10726 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3300233 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 82.42064 | 70.56477 | 26.04523 | 28.60591 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3303856 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 81.25953 | 61.53396 | 24.37324 | 28.78689 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 101 | 101 | 101 | 101 | 3304524 | 0.972614100 | 67.5305250 | 0 | ⋯ | 2 | 80.38717 | 63.49903 | 26.88744 | 30.82504 | 101 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3305901 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 79.36511 | 59.78857 | 24.47831 | 28.80120 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3306156 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 73.50676 | 52.37489 | 25.45713 | 30.16730 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 6 | 6 | 6 | 6 | 3304003 | 0.510871350 | 21.4316330 | 0 | ⋯ | 1 | 83.23574 | 64.93241 | 25.29660 | 29.64949 | 2 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3302452 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 78.33643 | 60.33009 | 25.53619 | 29.68893 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 7 | 7 | 7 | 7 | 3304706 | 0.348500880 | 17.1274780 | 0 | ⋯ | 1 | 73.61337 | 52.42067 | 27.54944 | 32.46999 | 1 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 15 | 15 | 15 | 15 | 3304904 | 0.545851230 | 1.6138647 | 0 | ⋯ | 0 | 79.05109 | 61.79447 | 27.26167 | 31.13134 | 9 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3305554 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 82.18256 | 65.54550 | 26.83577 | 30.80979 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 47 | 47 | 47 | 47 | 3306305 | 0.999907700 | 17.3724690 | 0 | ⋯ | 1 | 82.60871 | 63.06744 | 24.87374 | 29.35997 | 41 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 2 | 2 | 2 | 2 | 3305307 | 0.687753800 | 25.9504340 | 0 | ⋯ | 0 | 75.63594 | 55.21280 | 26.70411 | 31.37603 | 2 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 26 | 26 | 26 | 26 | 3303401 | 0.826959700 | 12.7061700 | 0 | ⋯ | 1 | 81.83781 | 63.63916 | 23.10783 | 27.24156 | 8 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 16 | 16 | 16 | 16 | 3303906 | 0.625782850 | 5.2500670 | 0 | ⋯ | 2 | 81.73606 | 63.17373 | 23.26517 | 27.53083 | 5 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 2 | 2 | 2 | 2 | 3301504 | 0.816611400 | 9.5955480 | 0 | ⋯ | 0 | 79.46833 | 62.00381 | 25.00786 | 29.00450 | 2 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 4 | 4 | 4 | 4 | 3302858 | 0.611740500 | 2.3689806 | 0 | ⋯ | 0 | 79.18611 | 61.53004 | 27.12009 | 31.13714 | 3 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 39 | 39 | 39 | 39 | 3300100 | 0.065632865 | 21.5198540 | 0 | ⋯ | 1 | 86.25177 | 71.49449 | 23.72850 | 26.88484 | 27 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3305802 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 82.03913 | 63.90536 | 23.01339 | 27.12274 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3305752 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 81.93850 | 67.09837 | 26.35436 | 29.93817 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 8 | 8 | 8 | 8 | 3300951 | 0.920166100 | 91.2304700 | 0 | ⋯ | 1 | 79.45310 | 57.48151 | 25.65169 | 30.35103 | 8 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 9 | 9 | 9 | 9 | 3302056 | 0.127595770 | 65.5546650 | 0 | ⋯ | 1 | 70.68673 | 47.04804 | 27.96651 | 33.35920 | 6 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 18 | 18 | 18 | 18 | 3300803 | 0.916297800 | 33.4032330 | 0 | ⋯ | 1 | 83.50706 | 66.66836 | 25.70174 | 29.89114 | 18 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 0 | 0 | 0 | 0 | 3302809 | 0.000000000 | 0.0000000 | 0 | ⋯ | 0 | 82.31677 | 63.13503 | 25.32590 | 29.84663 | 0 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 3 | 3 | 3 | 3 | 3302270 | 0.637974300 | 3.1057508 | 0 | ⋯ | 0 | 80.96867 | 62.61081 | 26.61476 | 30.96807 | 3 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 1 | 1 | 1 | 1 | 3302106 | 0.963267900 | 4.3499064 | 0 | ⋯ | 0 | 74.15506 | 52.79231 | 27.75876 | 32.64360 | 1 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 17 | 17 | 17 | 17 | 3302007 | 0.425479170 | 12.7947490 | 0 | ⋯ | 2 | 83.49459 | 68.10229 | 26.29010 | 29.97330 | 15 | NA | NA | NA | NA |
| 2023-12-03 | 202349 | 2 | 2 | 2 | 2 | 3302403 | 0.012022004 | 0.7613479 | 0 | ⋯ | 0 | 80.02879 | 61.95936 | 26.00251 | 30.20889 | 2 | NA | NA | NA | NA |
In [ ]:
Copied!