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Merged
merged 1 commit into from
Aug 25, 2022
Merged

finished before demo -real one #45

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148 changes: 78 additions & 70 deletions Notebook_Time_Series_Silviu.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -131,13 +131,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
"[1.06 seconds] Normalized Region East Asia and Pacific\n",
"[2.28 seconds] Normalized Region Europe and Central Asia\n",
"[1.32 seconds] Normalized Region Latin America and Caribbean\n",
"[0.85 seconds] Normalized Region Middle East and North Africa\n",
"[0.11 seconds] Normalized Region North America\n",
"[0.43 seconds] Normalized Region South Asia\n",
"[2.16 seconds] Normalized Region Sub-Saharan Africa\n"
"[2.16 seconds] Normalized Region East Asia and Pacific\n",
"[6.21 seconds] Normalized Region Europe and Central Asia\n",
"[2.77 seconds] Normalized Region Latin America and Caribbean\n",
"[1.76 seconds] Normalized Region Middle East and North Africa\n",
"[0.22 seconds] Normalized Region North America\n",
"[0.85 seconds] Normalized Region South Asia\n",
"[4.90 seconds] Normalized Region Sub-Saharan Africa\n"
]
}
],
Expand Down Expand Up @@ -171,7 +171,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "1174b81b1ae14433a7cbcb21a6f4ee66",
"model_id": "d3efc234551346128632c5c0f5d0513d",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -185,7 +185,7 @@
{
"data": {
"text/plain": [
"<function __main__.timeWindowCountry(By, Zone, Threshold, Years)>"
"<function __main__.time_window_zone(by, zone, threshold, years)>"
]
},
"execution_count": 6,
Expand All @@ -194,41 +194,41 @@
}
],
"source": [
"def timeWindowCountry(By, Zone, Threshold , Years):\n",
"def time_window_zone(by, zone, threshold , years):\n",
" # Update Widget Status\n",
" if By == 'Country':\n",
" if by == 'Country':\n",
" if status_widget.filter_by != \"Country\":\n",
" status_widget.filter_by = \"Country\"\n",
" zone_drop.options = country_list\n",
" return\n",
" if status_widget.zone != Zone:\n",
" if status_widget.zone != zone:\n",
" #Search for entries of the country.\n",
" status_widget.data = df_gold_index.loc[df_gold_index.index.get_level_values('Country') == Zone]\n",
" status_widget.zone = Zone\n",
" status_widget.data = df_gold_index.loc[df_gold_index.index.get_level_values('Country') == zone]\n",
" status_widget.zone = zone\n",
"\n",
" elif By == 'Region':\n",
" elif by == 'Region':\n",
" if status_widget.filter_by != \"Region\":\n",
" status_widget.filter_by = \"Region\"\n",
" zone_drop.options = region_list\n",
" return\n",
" if status_widget.zone != Zone:\n",
" if status_widget.zone != zone:\n",
" #Search for entries of the country.\n",
" status_widget.data = countries_by_region[Zone] # load_by_region(Zone)\n",
" status_widget.zone = Zone\n",
" status_widget.data = countries_by_region[zone] # load_by_region(Zone)\n",
" status_widget.zone = zone\n",
" \n",
" # Update Widget Data\n",
" df_zone = status_widget.data\n",
" \n",
" #Load the selected year range and the global range.\n",
" df_time = searchTimeSeries(Threshold, Years[0], Years[1], True, df_zone)\n",
" df_global = searchTimeSeries(Threshold, Years[0], Years[1], False, df_zone)\n",
" df_time = searchTimeSeries(threshold, years[0], years[1], True, df_zone)\n",
" df_global = searchTimeSeries(threshold, years[0], years[1], False, df_zone)\n",
"\n",
" # Display Data\n",
" if Years[0] > Years[1]: return print(\"Please, select a valid range of years.\")\n",
" if years[0] > years[1]: return print(\"Please, select a valid range of years.\")\n",
" \n",
" space = \"\\xa0\" * 10\n",
" try:\n",
" df_time = styler_method(df_time, str(Years[0]) + '-' + str(Years[1]))._repr_html_()\n",
" df_time = styler_method(df_time, str(years[0]) + '-' + str(years[1]))._repr_html_()\n",
" except: \n",
" df_time = 'No indicators available for the selected parameters'\n",
" \n",
Expand Down Expand Up @@ -266,7 +266,7 @@
" description='Threshold:',\n",
")\n",
"\n",
"widgets.interact(timeWindowCountry, By = by_drop, Zone = zone_drop, Threshold = floatslider, Years = intslider)"
"widgets.interact(time_window_zone, by = by_drop, zone = zone_drop, threshold = floatslider, years = intslider)"
]
},
{
Expand All @@ -284,7 +284,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -311,12 +311,12 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"indicators = list(df_gold.columns[3:])\n",
"indicators.remove('GDP')"
"indicators = list(df_gold_index.columns)\n",
"indicators.remove('GDP')\n"
]
},
{
Expand All @@ -338,13 +338,13 @@
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f257d561549a4a4cacc5ff621a39e332",
"model_id": "9c7237ec068d4abd9ec6863b228fb0f2",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -358,31 +358,31 @@
{
"data": {
"text/plain": [
"<function __main__.tableHighCountry(By, Zone)>"
"<function __main__.table_high_country(by, zone)>"
]
},
"execution_count": 18,
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def tableHighCountry(By, Zone):\n",
" if By == 'Country':\n",
" if len(zone_drop.options) == len(region_list): \n",
" zone_drop.options = country_list\n",
"def table_high_country(by, zone):\n",
" if by == 'Country':\n",
" if len(zone_drop_high.options) == len(region_list): \n",
" zone_drop_high.options = country_list\n",
" return\n",
" #Search for the entries of the country.\n",
" df_zone = df_gold_index.loc[df_gold_index.index.get_level_values('Country') == Zone]\n",
" df_zone = df_gold_index.loc[df_gold_index.index.get_level_values('Country') == zone]\n",
" min_diff = 5\n",
" \n",
" \n",
" elif By == 'Region':\n",
" if len(zone_drop.options) == len(country_list): \n",
" zone_drop.options = region_list\n",
" elif by == 'Region':\n",
" if len(zone_drop_high.options) == len(country_list): \n",
" zone_drop_high.options = region_list\n",
" return\n",
" #Search for the entries of the region and normalize.\n",
" df_zone = countries_by_region[Zone]\n",
" df_zone = countries_by_region[zone]\n",
" min_diff = 2\n",
" \n",
" df_highest = init_highest_table()\n",
Expand Down Expand Up @@ -426,18 +426,18 @@
"\n",
" display(df_highest)\n",
"\n",
"by_drop = widgets.Dropdown(\n",
"by_drop_high = widgets.Dropdown(\n",
" options= ['Country', 'Region'],\n",
" description='By: ',\n",
")\n",
"\n",
"zone_drop = widgets.Dropdown(\n",
"zone_drop_high = widgets.Dropdown(\n",
" options= country_list,\n",
" value ='Afghanistan',\n",
" description='Zone:',\n",
")\n",
"\n",
"widgets.interact(tableHighCountry, By = by_drop, Zone = zone_drop)\n"
"widgets.interact(table_high_country, by = by_drop_high, zone = zone_drop_high)\n"
]
},
{
Expand All @@ -451,18 +451,18 @@
},
{
"cell_type": "code",
"execution_count": 31,
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "8ded79576a674a89989070716a2e6336",
"model_id": "a2e489fb3c2e434f83f9dc653282f411",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"interactive(children=(Dropdown(description='Country: ', options=('Afghanistan', 'Albania', 'Algeria', 'Angola'…"
"interactive(children=(Dropdown(description='By: ', options=('Country', 'Region'), value='Country'), Dropdown(d…"
]
},
"metadata": {},
Expand All @@ -471,46 +471,61 @@
{
"data": {
"text/plain": [
"<function __main__.plotYearRange(Zone, Indicator, Years)>"
"<function __main__.plot_year_range(by, zone, indicator, years)>"
]
},
"execution_count": 31,
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"indicators = list(df_gold_index.columns)\n",
"indicators.remove('GDP')\n",
"\n",
"def plotYearRange(Zone, Indicator, Years):\n",
" df_aux = df_gold_index.loc[df_gold_index.index.get_level_values('Country') == Zone]\n",
" df_aux = df_aux.loc[(df_aux.index.get_level_values(\"Year\") >= Years[0]) & (df_aux.index.get_level_values(\"Year\") <= Years[1])]\n",
" spear = stats.spearmanr(df_aux[Indicator], df_aux['GDP'])\n",
" df_aux = normalize_by_country(df_aux).reset_index(drop=False)\n",
"def plot_year_range(by, zone, indicator, years):\n",
" if by == 'Country':\n",
" if list(zone_drop_plot.options) != country_list:\n",
" zone_drop_plot.options = country_list\n",
" return\n",
" df_zone = df_gold_index.loc[df_gold_index.index.get_level_values('Country') == zone]\n",
" \n",
" elif by == 'Region':\n",
" if list(zone_drop_plot.options) != region_list:\n",
" zone_drop_plot.options = region_list\n",
" return\n",
" df_zone = countries_by_region[zone]\n",
"\n",
" df_zone = df_zone.loc[(df_zone.index.get_level_values(\"Year\") >= years[0]) & (df_zone.index.get_level_values(\"Year\") <= years[1])]\n",
" spear = stats.spearmanr(df_zone[indicator], df_zone['GDP'])\n",
" df_zone = normalize_by_country(df_zone)\n",
"\n",
"\n",
" #In case if by is region it groups by year.\n",
" df_zone = df_zone.loc[df_zone.index.get_level_values(by_drop_plot.value) == zone, ['GDP', indicator]].groupby(level = 'Year').median()\n",
"\n",
" print(spear)\n",
" plt.figure(figsize=(6,6))\n",
" plt.plot(df_aux[\"Year\"], df_aux[\"GDP\"], color=\"red\", label = 'GDP')\n",
" plt.plot(df_aux[\"Year\"], df_aux[Indicator], color=\"green\", label = Indicator)\n",
" plt.plot(df_zone.index.get_level_values(\"Year\"), df_zone[\"GDP\"], color=\"red\", label = 'GDP')\n",
" plt.plot(df_zone.index.get_level_values(\"Year\"), df_zone[indicator], color=\"green\", label = indicator)\n",
" plt.legend(loc=\"lower right\")\n",
" \n",
"by_drop_plot = widgets.Dropdown(\n",
" options= ['Country', 'Region'],\n",
" description='By: ',\n",
")\n",
"\n",
"\n",
"\n",
"country_drop = widgets.Dropdown(\n",
"zone_drop_plot = widgets.Dropdown(\n",
" options= country_list,\n",
" value='Afghanistan',\n",
" description='Country: ',\n",
")\n",
"\n",
"indicator_drop = widgets.Dropdown(\n",
"indicator_drop_plot = widgets.Dropdown(\n",
" options= sorted(indicators),\n",
" value='AgriShareGDP',\n",
" description='Indicator: :',\n",
")\n",
"\n",
"intslider = widgets.IntRangeSlider(\n",
"intslider_plot = widgets.IntRangeSlider(\n",
" value=[min(set(df_gold['Year'])), max(set(df_gold['Year']))],\n",
" min= min(set(df_gold['Year'])),\n",
" max= max(set(df_gold['Year'])),\n",
Expand All @@ -520,15 +535,8 @@
"\n",
"# TODO By Region: Say Y axis is Qualitative (Not real values but Normalized to observe evolution vs GDP - Tendendency)\n",
"\n",
"widgets.interact(plotYearRange, Zone = country_drop, Indicator = indicator_drop, Years = intslider)"
"widgets.interact(plot_year_range, by = by_drop_plot, zone = zone_drop_plot, indicator = indicator_drop_plot, years = intslider_plot)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand Down