# - permalink: /covid-world-progress/
# - image: images/world-infected.png
# - toc: false
# - hide: false
# - sticky_rank: 3
# -
# > Important: This dashboard contains the results of a predictive model that was not built by an epidemiologist.
# + papermill={"duration": 0.330834, "end_time": "2020-03-27T06:31:16.261108", "exception": false, "start_time": "2020-03-27T06:31:15.930274", "status": "completed"} tags=[]
#hide
import pandas as pd
import covid_helpers
covid_data = covid_helpers.CovidData()
stylers = covid_helpers.PandasStyling
df_all = covid_data.table_with_projections()
# -
#hide_input
from IPython.display import Markdown
Markdown(f"*Based on data up to:* ***{covid_data.cur_date}***")
# +
#hide
_, debug_dfs = covid_data.table_with_projections(debug_dfs=True)
df_alt = pd.concat([d.reset_index() for d in debug_dfs], axis=0)
# -
# > Warning: This dashboard was not built by an epidemiologist.
# > Note: Click a country name to open a search results page for that country's COVID-19 news.
# +
#hide
import pandas as pd
import covid_helpers as covid_helpers
stylers = covid_helpers.PandasStyling
# +
#hide
day_diff = 10
cur_data = covid_helpers.CovidData()
df_cur_all, debug_dfs = cur_data.table_with_projections(projection_days=[30], debug_dfs=True)
df_cur = cur_data.filter_df(df_cur_all)
past_data = covid_helpers.CovidData(-day_diff)
df_past = past_data.filter_df(past_data.table_with_projections(projection_days=[day_diff-1]))
# -
#hide_input
from IPython.display import Markdown
past_date = pd.to_datetime(past_data.dt_cols[-1]).date().isoformat()
Markdown(f"***Based on data up to: {cur_data.cur_date}. \
Compared to ({day_diff} days before): {past_date}***")
# +