diff --git a/COVID.ipynb b/COVID.ipynb
index 51b86bd..751aa9c 100644
--- a/COVID.ipynb
+++ b/COVID.ipynb
@@ -21,157 +21,172 @@
},
{
"cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "scrolled": true
- },
+ "execution_count": 5,
+ "metadata": {},
"outputs": [
{
"data": {
"text/html": [
- "
| DateRep | Day | Month | Year | NewConfCases | Deaths | CountryExp | GeoId | Country Code |
---|
| String | Int64 | Int64 | Int64 | Int64 | Int64 | String | String | String⍰ |
---|
5 rows × 10 columns (omitted printing of 1 columns)
1 | 3/26/2020 | 26 | 3 | 2020 | 33 | 0 | Afghanistan | AF | AFG |
---|
2 | 3/25/2020 | 25 | 3 | 2020 | 2 | 0 | Afghanistan | AF | AFG |
---|
3 | 3/24/2020 | 24 | 3 | 2020 | 6 | 1 | Afghanistan | AF | AFG |
---|
4 | 3/23/2020 | 23 | 3 | 2020 | 10 | 0 | Afghanistan | AF | AFG |
---|
5 | 3/22/2020 | 22 | 3 | 2020 | 0 | 0 | Afghanistan | AF | AFG |
---|
"
+ " | dateRep | day | month | year | cases | deaths | countriesAndTerritories | geoId |
---|
| String | Int64 | Int64 | Int64 | Int64 | Int64 | String | String |
---|
5 rows × 10 columns (omitted printing of 2 columns)
1 | 30/03/2020 | 30 | 3 | 2020 | 8 | 1 | Afghanistan | AF |
---|
2 | 29/03/2020 | 29 | 3 | 2020 | 15 | 1 | Afghanistan | AF |
---|
3 | 28/03/2020 | 28 | 3 | 2020 | 16 | 1 | Afghanistan | AF |
---|
4 | 27/03/2020 | 27 | 3 | 2020 | 0 | 0 | Afghanistan | AF |
---|
5 | 26/03/2020 | 26 | 3 | 2020 | 33 | 0 | Afghanistan | AF |
---|
"
],
"text/latex": [
- "\\begin{tabular}{r|cccccccccc}\n",
- "\t& DateRep & Day & Month & Year & NewConfCases & Deaths & CountryExp & GeoId & Country Code & \\\\\n",
+ "\\begin{tabular}{r|ccccccccc}\n",
+ "\t& dateRep & day & month & year & cases & deaths & countriesAndTerritories & geoId & \\\\\n",
"\t\\hline\n",
- "\t& String & Int64 & Int64 & Int64 & Int64 & Int64 & String & String & String⍰ & \\\\\n",
+ "\t& String & Int64 & Int64 & Int64 & Int64 & Int64 & String & String & \\\\\n",
"\t\\hline\n",
- "\t1 & 3/26/2020 & 26 & 3 & 2020 & 33 & 0 & Afghanistan & AF & AFG & $\\dots$ \\\\\n",
- "\t2 & 3/25/2020 & 25 & 3 & 2020 & 2 & 0 & Afghanistan & AF & AFG & $\\dots$ \\\\\n",
- "\t3 & 3/24/2020 & 24 & 3 & 2020 & 6 & 1 & Afghanistan & AF & AFG & $\\dots$ \\\\\n",
- "\t4 & 3/23/2020 & 23 & 3 & 2020 & 10 & 0 & Afghanistan & AF & AFG & $\\dots$ \\\\\n",
- "\t5 & 3/22/2020 & 22 & 3 & 2020 & 0 & 0 & Afghanistan & AF & AFG & $\\dots$ \\\\\n",
+ "\t1 & 30/03/2020 & 30 & 3 & 2020 & 8 & 1 & Afghanistan & AF & $\\dots$ \\\\\n",
+ "\t2 & 29/03/2020 & 29 & 3 & 2020 & 15 & 1 & Afghanistan & AF & $\\dots$ \\\\\n",
+ "\t3 & 28/03/2020 & 28 & 3 & 2020 & 16 & 1 & Afghanistan & AF & $\\dots$ \\\\\n",
+ "\t4 & 27/03/2020 & 27 & 3 & 2020 & 0 & 0 & Afghanistan & AF & $\\dots$ \\\\\n",
+ "\t5 & 26/03/2020 & 26 & 3 & 2020 & 33 & 0 & Afghanistan & AF & $\\dots$ \\\\\n",
"\\end{tabular}\n"
],
"text/plain": [
"5×10 DataFrame. Omitted printing of 4 columns\n",
- "│ Row │ DateRep │ Day │ Month │ Year │ NewConfCases │ Deaths │\n",
- "│ │ \u001b[90mString\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │\n",
- "├─────┼───────────┼───────┼───────┼───────┼──────────────┼────────┤\n",
- "│ 1 │ 3/26/2020 │ 26 │ 3 │ 2020 │ 33 │ 0 │\n",
- "│ 2 │ 3/25/2020 │ 25 │ 3 │ 2020 │ 2 │ 0 │\n",
- "│ 3 │ 3/24/2020 │ 24 │ 3 │ 2020 │ 6 │ 1 │\n",
- "│ 4 │ 3/23/2020 │ 23 │ 3 │ 2020 │ 10 │ 0 │\n",
- "│ 5 │ 3/22/2020 │ 22 │ 3 │ 2020 │ 0 │ 0 │"
+ "│ Row │ dateRep │ day │ month │ year │ cases │ deaths │\n",
+ "│ │ \u001b[90mString\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │\n",
+ "├─────┼────────────┼───────┼───────┼───────┼───────┼────────┤\n",
+ "│ 1 │ 30/03/2020 │ 30 │ 3 │ 2020 │ 8 │ 1 │\n",
+ "│ 2 │ 29/03/2020 │ 29 │ 3 │ 2020 │ 15 │ 1 │\n",
+ "│ 3 │ 28/03/2020 │ 28 │ 3 │ 2020 │ 16 │ 1 │\n",
+ "│ 4 │ 27/03/2020 │ 27 │ 3 │ 2020 │ 0 │ 0 │\n",
+ "│ 5 │ 26/03/2020 │ 26 │ 3 │ 2020 │ 33 │ 0 │"
]
},
- "execution_count": 2,
+ "execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
+ "download(\"https://opendata.ecdc.europa.eu/covid19/casedistribution/csv\", \"covid.csv\")\n",
"data = CSV.read(\"covid.csv\")\n",
- "rename!(data, Dict(\n",
- " Symbol(\"Countries and territories\") => \"CountryExp\",\n",
- " :Cases => \"NewConfCases\"\n",
- " ))\n",
"first(data, 5)"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 7,
"metadata": {
"scrolled": true
},
"outputs": [
{
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "┌ Warning: `getindex(df::DataFrame, col_ind::ColumnIndex)` is deprecated, use `df[!, col_ind]` instead.\n",
- "│ caller = top-level scope at In[4]:1\n",
- "└ @ Core In[4]:1\n"
+ "ename": "ArgumentError",
+ "evalue": "ArgumentError: Tried renaming :countriesAndTerritories to :CountryExp, when :countriesAndTerritories does not exist in the Index.",
+ "output_type": "error",
+ "traceback": [
+ "ArgumentError: Tried renaming :countriesAndTerritories to :CountryExp, when :countriesAndTerritories does not exist in the Index.",
+ "",
+ "Stacktrace:",
+ " [1] rename!(::DataFrames.Index, ::Array{Pair{Symbol,Symbol},1}) at /home/abel/.julia/packages/DataFrames/uPgZV/src/other/index.jl:70",
+ " [2] rename!(::DataFrame, ::Dict{Symbol,String}) at /home/abel/.julia/packages/DataFrames/uPgZV/src/abstractdataframe/abstractdataframe.jl:170",
+ " [3] top-level scope at In[7]:1"
]
- },
+ }
+ ],
+ "source": [
+ "rename!(data, Dict(\n",
+ " Symbol(\"countriesAndTerritories\") => \"CountryExp\",\n",
+ " :cases => \"NewConfCases\"\n",
+ " ))\n",
+ "first(data, 5)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
{
"data": {
"text/html": [
- " | DateRep | Day | Month | Year | NewConfCases | Deaths | CountryExp | GeoId | Country Code |
---|
| String | Int64 | Int64 | Int64 | Int64 | Int64 | String | String | String⍰ |
---|
84 rows × 10 columns (omitted printing of 1 columns)
1 | 3/26/2020 | 26 | 3 | 2020 | 232 | 11 | Brazil | BR | BRA |
---|
2 | 3/25/2020 | 25 | 3 | 2020 | 310 | 12 | Brazil | BR | BRA |
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3 | 3/24/2020 | 24 | 3 | 2020 | 345 | 9 | Brazil | BR | BRA |
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4 | 3/23/2020 | 23 | 3 | 2020 | 418 | 7 | Brazil | BR | BRA |
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5 | 3/22/2020 | 22 | 3 | 2020 | 224 | 7 | Brazil | BR | BRA |
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6 | 3/21/2020 | 21 | 3 | 2020 | 283 | 5 | Brazil | BR | BRA |
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7 | 3/20/2020 | 20 | 3 | 2020 | 193 | 2 | Brazil | BR | BRA |
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8 | 3/19/2020 | 19 | 3 | 2020 | 137 | 3 | Brazil | BR | BRA |
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9 | 3/18/2020 | 18 | 3 | 2020 | 57 | 1 | Brazil | BR | BRA |
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10 | 3/17/2020 | 17 | 3 | 2020 | 34 | 0 | Brazil | BR | BRA |
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11 | 3/16/2020 | 16 | 3 | 2020 | 79 | 0 | Brazil | BR | BRA |
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12 | 3/15/2020 | 15 | 3 | 2020 | 23 | 0 | Brazil | BR | BRA |
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13 | 3/14/2020 | 14 | 3 | 2020 | 21 | 0 | Brazil | BR | BRA |
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14 | 3/13/2020 | 13 | 3 | 2020 | 25 | 0 | Brazil | BR | BRA |
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15 | 3/12/2020 | 12 | 3 | 2020 | 18 | 0 | Brazil | BR | BRA |
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16 | 3/11/2020 | 11 | 3 | 2020 | 9 | 0 | Brazil | BR | BRA |
---|
17 | 3/9/2020 | 9 | 3 | 2020 | 12 | 0 | Brazil | BR | BRA |
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18 | 3/8/2020 | 8 | 3 | 2020 | 0 | 0 | Brazil | BR | BRA |
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19 | 3/7/2020 | 7 | 3 | 2020 | 5 | 0 | Brazil | BR | BRA |
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20 | 3/6/2020 | 6 | 3 | 2020 | 5 | 0 | Brazil | BR | BRA |
---|
21 | 3/5/2020 | 5 | 3 | 2020 | 1 | 0 | Brazil | BR | BRA |
---|
22 | 3/2/2020 | 2 | 3 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
23 | 3/1/2020 | 1 | 3 | 2020 | 1 | 0 | Brazil | BR | BRA |
---|
24 | 2/29/2020 | 29 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
25 | 2/28/2020 | 28 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
26 | 2/27/2020 | 27 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
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27 | 2/26/2020 | 26 | 2 | 2020 | 1 | 0 | Brazil | BR | BRA |
---|
28 | 2/25/2020 | 25 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
29 | 2/24/2020 | 24 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
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30 | 2/23/2020 | 23 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |
---|
"
+ " | dateRep | day | month | year | NewConfCases | deaths | CountryExp | geoId | countryterritoryCode |
---|
| String | Int64 | Int64 | Int64 | Int64 | Int64 | String | String | String⍰ |
---|
88 rows × 10 columns (omitted printing of 1 columns)
1 | 30/03/2020 | 30 | 3 | 2020 | 352 | 22 | Brazil | BR | BRA |
---|
2 | 29/03/2020 | 29 | 3 | 2020 | 487 | 22 | Brazil | BR | BRA |
---|
3 | 28/03/2020 | 28 | 3 | 2020 | 502 | 15 | Brazil | BR | BRA |
---|
4 | 27/03/2020 | 27 | 3 | 2020 | 482 | 20 | Brazil | BR | BRA |
---|
5 | 26/03/2020 | 26 | 3 | 2020 | 232 | 11 | Brazil | BR | BRA |
---|
6 | 25/03/2020 | 25 | 3 | 2020 | 310 | 12 | Brazil | BR | BRA |
---|
7 | 24/03/2020 | 24 | 3 | 2020 | 345 | 9 | Brazil | BR | BRA |
---|
8 | 23/03/2020 | 23 | 3 | 2020 | 418 | 7 | Brazil | BR | BRA |
---|
9 | 22/03/2020 | 22 | 3 | 2020 | 224 | 7 | Brazil | BR | BRA |
---|
10 | 21/03/2020 | 21 | 3 | 2020 | 283 | 5 | Brazil | BR | BRA |
---|
11 | 20/03/2020 | 20 | 3 | 2020 | 193 | 2 | Brazil | BR | BRA |
---|
12 | 19/03/2020 | 19 | 3 | 2020 | 137 | 3 | Brazil | BR | BRA |
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13 | 18/03/2020 | 18 | 3 | 2020 | 57 | 1 | Brazil | BR | BRA |
---|
14 | 17/03/2020 | 17 | 3 | 2020 | 34 | 0 | Brazil | BR | BRA |
---|
15 | 16/03/2020 | 16 | 3 | 2020 | 79 | 0 | Brazil | BR | BRA |
---|
16 | 15/03/2020 | 15 | 3 | 2020 | 23 | 0 | Brazil | BR | BRA |
---|
17 | 14/03/2020 | 14 | 3 | 2020 | 21 | 0 | Brazil | BR | BRA |
---|
18 | 13/03/2020 | 13 | 3 | 2020 | 25 | 0 | Brazil | BR | BRA |
---|
19 | 12/03/2020 | 12 | 3 | 2020 | 18 | 0 | Brazil | BR | BRA |
---|
20 | 11/03/2020 | 11 | 3 | 2020 | 9 | 0 | Brazil | BR | BRA |
---|
21 | 09/03/2020 | 9 | 3 | 2020 | 12 | 0 | Brazil | BR | BRA |
---|
22 | 08/03/2020 | 8 | 3 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
23 | 07/03/2020 | 7 | 3 | 2020 | 5 | 0 | Brazil | BR | BRA |
---|
24 | 06/03/2020 | 6 | 3 | 2020 | 5 | 0 | Brazil | BR | BRA |
---|
25 | 05/03/2020 | 5 | 3 | 2020 | 1 | 0 | Brazil | BR | BRA |
---|
26 | 02/03/2020 | 2 | 3 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
27 | 01/03/2020 | 1 | 3 | 2020 | 1 | 0 | Brazil | BR | BRA |
---|
28 | 29/02/2020 | 29 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
29 | 28/02/2020 | 28 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
30 | 27/02/2020 | 27 | 2 | 2020 | 0 | 0 | Brazil | BR | BRA |
---|
⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |
---|
"
],
"text/latex": [
"\\begin{tabular}{r|cccccccccc}\n",
- "\t& DateRep & Day & Month & Year & NewConfCases & Deaths & CountryExp & GeoId & Country Code & \\\\\n",
+ "\t& dateRep & day & month & year & NewConfCases & deaths & CountryExp & geoId & countryterritoryCode & \\\\\n",
"\t\\hline\n",
"\t& String & Int64 & Int64 & Int64 & Int64 & Int64 & String & String & String⍰ & \\\\\n",
"\t\\hline\n",
- "\t1 & 3/26/2020 & 26 & 3 & 2020 & 232 & 11 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t2 & 3/25/2020 & 25 & 3 & 2020 & 310 & 12 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t3 & 3/24/2020 & 24 & 3 & 2020 & 345 & 9 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t4 & 3/23/2020 & 23 & 3 & 2020 & 418 & 7 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t5 & 3/22/2020 & 22 & 3 & 2020 & 224 & 7 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t6 & 3/21/2020 & 21 & 3 & 2020 & 283 & 5 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t7 & 3/20/2020 & 20 & 3 & 2020 & 193 & 2 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t8 & 3/19/2020 & 19 & 3 & 2020 & 137 & 3 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t9 & 3/18/2020 & 18 & 3 & 2020 & 57 & 1 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t10 & 3/17/2020 & 17 & 3 & 2020 & 34 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t11 & 3/16/2020 & 16 & 3 & 2020 & 79 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t12 & 3/15/2020 & 15 & 3 & 2020 & 23 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t13 & 3/14/2020 & 14 & 3 & 2020 & 21 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t14 & 3/13/2020 & 13 & 3 & 2020 & 25 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t15 & 3/12/2020 & 12 & 3 & 2020 & 18 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t16 & 3/11/2020 & 11 & 3 & 2020 & 9 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t17 & 3/9/2020 & 9 & 3 & 2020 & 12 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t18 & 3/8/2020 & 8 & 3 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t19 & 3/7/2020 & 7 & 3 & 2020 & 5 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t20 & 3/6/2020 & 6 & 3 & 2020 & 5 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t21 & 3/5/2020 & 5 & 3 & 2020 & 1 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t22 & 3/2/2020 & 2 & 3 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t23 & 3/1/2020 & 1 & 3 & 2020 & 1 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t24 & 2/29/2020 & 29 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t25 & 2/28/2020 & 28 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t26 & 2/27/2020 & 27 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t27 & 2/26/2020 & 26 & 2 & 2020 & 1 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t28 & 2/25/2020 & 25 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t29 & 2/24/2020 & 24 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
- "\t30 & 2/23/2020 & 23 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t1 & 30/03/2020 & 30 & 3 & 2020 & 352 & 22 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t2 & 29/03/2020 & 29 & 3 & 2020 & 487 & 22 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t3 & 28/03/2020 & 28 & 3 & 2020 & 502 & 15 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t4 & 27/03/2020 & 27 & 3 & 2020 & 482 & 20 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t5 & 26/03/2020 & 26 & 3 & 2020 & 232 & 11 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t6 & 25/03/2020 & 25 & 3 & 2020 & 310 & 12 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t7 & 24/03/2020 & 24 & 3 & 2020 & 345 & 9 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t8 & 23/03/2020 & 23 & 3 & 2020 & 418 & 7 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t9 & 22/03/2020 & 22 & 3 & 2020 & 224 & 7 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t10 & 21/03/2020 & 21 & 3 & 2020 & 283 & 5 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t11 & 20/03/2020 & 20 & 3 & 2020 & 193 & 2 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t12 & 19/03/2020 & 19 & 3 & 2020 & 137 & 3 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t13 & 18/03/2020 & 18 & 3 & 2020 & 57 & 1 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t14 & 17/03/2020 & 17 & 3 & 2020 & 34 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t15 & 16/03/2020 & 16 & 3 & 2020 & 79 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t16 & 15/03/2020 & 15 & 3 & 2020 & 23 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t17 & 14/03/2020 & 14 & 3 & 2020 & 21 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t18 & 13/03/2020 & 13 & 3 & 2020 & 25 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t19 & 12/03/2020 & 12 & 3 & 2020 & 18 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t20 & 11/03/2020 & 11 & 3 & 2020 & 9 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t21 & 09/03/2020 & 9 & 3 & 2020 & 12 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t22 & 08/03/2020 & 8 & 3 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t23 & 07/03/2020 & 7 & 3 & 2020 & 5 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t24 & 06/03/2020 & 6 & 3 & 2020 & 5 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t25 & 05/03/2020 & 5 & 3 & 2020 & 1 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t26 & 02/03/2020 & 2 & 3 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t27 & 01/03/2020 & 1 & 3 & 2020 & 1 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t28 & 29/02/2020 & 29 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t29 & 28/02/2020 & 28 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
+ "\t30 & 27/02/2020 & 27 & 2 & 2020 & 0 & 0 & Brazil & BR & BRA & $\\dots$ \\\\\n",
"\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & \\\\\n",
"\\end{tabular}\n"
],
"text/plain": [
- "84×10 DataFrame. Omitted printing of 4 columns\n",
- "│ Row │ DateRep │ Day │ Month │ Year │ NewConfCases │ Deaths │\n",
+ "88×10 DataFrame. Omitted printing of 4 columns\n",
+ "│ Row │ dateRep │ day │ month │ year │ NewConfCases │ deaths │\n",
"│ │ \u001b[90mString\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │ \u001b[90mInt64\u001b[39m │\n",
"├─────┼────────────┼───────┼───────┼───────┼──────────────┼────────┤\n",
- "│ 1 │ 3/26/2020 │ 26 │ 3 │ 2020 │ 232 │ 11 │\n",
- "│ 2 │ 3/25/2020 │ 25 │ 3 │ 2020 │ 310 │ 12 │\n",
- "│ 3 │ 3/24/2020 │ 24 │ 3 │ 2020 │ 345 │ 9 │\n",
- "│ 4 │ 3/23/2020 │ 23 │ 3 │ 2020 │ 418 │ 7 │\n",
- "│ 5 │ 3/22/2020 │ 22 │ 3 │ 2020 │ 224 │ 7 │\n",
- "│ 6 │ 3/21/2020 │ 21 │ 3 │ 2020 │ 283 │ 5 │\n",
- "│ 7 │ 3/20/2020 │ 20 │ 3 │ 2020 │ 193 │ 2 │\n",
- "│ 8 │ 3/19/2020 │ 19 │ 3 │ 2020 │ 137 │ 3 │\n",
- "│ 9 │ 3/18/2020 │ 18 │ 3 │ 2020 │ 57 │ 1 │\n",
- "│ 10 │ 3/17/2020 │ 17 │ 3 │ 2020 │ 34 │ 0 │\n",
+ "│ 1 │ 30/03/2020 │ 30 │ 3 │ 2020 │ 352 │ 22 │\n",
+ "│ 2 │ 29/03/2020 │ 29 │ 3 │ 2020 │ 487 │ 22 │\n",
+ "│ 3 │ 28/03/2020 │ 28 │ 3 │ 2020 │ 502 │ 15 │\n",
+ "│ 4 │ 27/03/2020 │ 27 │ 3 │ 2020 │ 482 │ 20 │\n",
+ "│ 5 │ 26/03/2020 │ 26 │ 3 │ 2020 │ 232 │ 11 │\n",
+ "│ 6 │ 25/03/2020 │ 25 │ 3 │ 2020 │ 310 │ 12 │\n",
+ "│ 7 │ 24/03/2020 │ 24 │ 3 │ 2020 │ 345 │ 9 │\n",
+ "│ 8 │ 23/03/2020 │ 23 │ 3 │ 2020 │ 418 │ 7 │\n",
+ "│ 9 │ 22/03/2020 │ 22 │ 3 │ 2020 │ 224 │ 7 │\n",
+ "│ 10 │ 21/03/2020 │ 21 │ 3 │ 2020 │ 283 │ 5 │\n",
"⋮\n",
- "│ 74 │ 1/10/2020 │ 10 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 75 │ 1/9/2020 │ 9 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 76 │ 1/8/2020 │ 8 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 77 │ 1/7/2020 │ 7 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 78 │ 1/6/2020 │ 6 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 79 │ 1/5/2020 │ 5 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 80 │ 1/4/2020 │ 4 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 81 │ 1/3/2020 │ 3 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 82 │ 1/2/2020 │ 2 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 83 │ 1/1/2020 │ 1 │ 1 │ 2020 │ 0 │ 0 │\n",
- "│ 84 │ 12/31/2019 │ 31 │ 12 │ 2019 │ 0 │ 0 │"
+ "│ 78 │ 10/01/2020 │ 10 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 79 │ 09/01/2020 │ 9 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 80 │ 08/01/2020 │ 8 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 81 │ 07/01/2020 │ 7 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 82 │ 06/01/2020 │ 6 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 83 │ 05/01/2020 │ 5 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 84 │ 04/01/2020 │ 4 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 85 │ 03/01/2020 │ 3 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 86 │ 02/01/2020 │ 2 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 87 │ 01/01/2020 │ 1 │ 1 │ 2020 │ 0 │ 0 │\n",
+ "│ 88 │ 31/12/2019 │ 31 │ 12 │ 2019 │ 0 │ 0 │"
]
},
- "execution_count": 4,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "df = data[findall(data[:CountryExp] .== \"Brazil\"),:]\n",
+ "df = data[findall(data.CountryExp .== \"Brazil\"),:]\n",
"df"
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
@@ -180,7 +195,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 12,
"metadata": {},
"outputs": [
{
@@ -189,208 +204,223 @@
"\n",
"\n"
]
},
- "execution_count": 6,
+ "execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "scatter(y[findfirst(y .> 0):end])"
+ "scatter(y[findfirst(y .> 0):end], leg=false)"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "27-element Array{Int64,1}:\n",
+ "31-element Array{Int64,1}:\n",
" 1\n",
" 0\n",
" 0\n",
@@ -405,10 +435,6 @@
" 9\n",
" 18\n",
" ⋮\n",
- " 23\n",
- " 79\n",
- " 34\n",
- " 57\n",
" 137\n",
" 193\n",
" 283\n",
@@ -416,10 +442,14 @@
" 418\n",
" 345\n",
" 310\n",
- " 232"
+ " 232\n",
+ " 482\n",
+ " 502\n",
+ " 487\n",
+ " 352"
]
},
- "execution_count": 7,
+ "execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@@ -431,7 +461,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
@@ -440,180 +470,206 @@
"\n",
"\n"
]
},
- "execution_count": 8,
+ "execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
@@ -622,6 +678,201 @@
"scatter(y, ms=3, leg=false)"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n"
+ ]
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "scatter(cumsum(y), ms=3, leg=false)"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -631,7 +882,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
@@ -640,163 +891,163 @@
"\n",
"\n"
]
},
- "execution_count": 9,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
@@ -820,7 +1071,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -829,134 +1080,134 @@
"\n",
"