愛了！Python 動態(tài)圖表太太太秀了！

import?pandas_alive
import?pandas?as?pd

covid_df?=?pd.read_csv('data/covid19.csv',?index_col=0,?parse_dates=[0])
covid_df.plot_animated(filename='examples/example-barh-chart.gif',?n_visible=15)

elec_df?=?pd.read_csv("data/Aus_Elec_Gen_1980_2018.csv",?index_col=0,?parse_dates=[0],?thousands=',')
elec_df?=?elec_df.iloc[:20,?:]
elec_df.fillna(0).plot_animated('examples/example-electricity-generated-australia.gif',?period_fmt="%Y",
????????????????????????????????title='Australian?Electricity?Generation?Sources?1980-2018')

covid_df?=?pd.read_csv('data/covid19.csv',?index_col=0,?parse_dates=[0])
covid_df.plot_animated(filename='examples/example-barv-chart.gif',?orientation='v',?n_visible=15)

covid_df?=?pd.read_csv('data/covid19.csv',?index_col=0,?parse_dates=[0])
covid_df.diff().fillna(0).plot_animated(filename='examples/example-line-chart.gif',?kind='line',?period_label={'x':?0.25,?'y':?0.9})

covid_df?=?pd.read_csv('data/covid19.csv',?index_col=0,?parse_dates=[0])
covid_df.sum(axis=1).fillna(0).plot_animated(filename='examples/example-bar-chart.gif',?kind='bar',
????????period_label={'x':?0.1,?'y':?0.9},
????????enable_progress_bar=True,?steps_per_period=2,?interpolate_period=True,?period_length=200
)

max_temp_df?=?pd.read_csv(
????"data/Newcastle_Australia_Max_Temps.csv",
????parse_dates={"Timestamp":?["Year",?"Month",?"Day"]},
)
min_temp_df?=?pd.read_csv(
????"data/Newcastle_Australia_Min_Temps.csv",
????parse_dates={"Timestamp":?["Year",?"Month",?"Day"]},
)

max_temp_df?=?max_temp_df.iloc[:5000,?:]
min_temp_df?=?min_temp_df.iloc[:5000,?:]

merged_temp_df?=?pd.merge_asof(max_temp_df,?min_temp_df,?on="Timestamp")
merged_temp_df.index?=?pd.to_datetime(merged_temp_df["Timestamp"].dt.strftime('%Y/%m/%d'))

keep_columns?=?["Minimum?temperature?(Degree?C)",?"Maximum?temperature?(Degree?C)"]
merged_temp_df[keep_columns].resample("Y").mean().plot_animated(filename='examples/example-scatter-chart.gif',?kind="scatter",
????????????????????????????????????????????????????????????????title='Max?&?Min?Temperature?Newcastle,?Australia')

covid_df?=?pd.read_csv('data/covid19.csv',?index_col=0,?parse_dates=[0])
covid_df.plot_animated(filename='examples/example-pie-chart.gif',?kind="pie",
???????????????????????rotatelabels=True,?period_label={'x':?0,?'y':?0})

multi_index_df?=?pd.read_csv("data/multi.csv",?header=[0,?1],?index_col=0)
multi_index_df.index?=?pd.to_datetime(multi_index_df.index,?dayfirst=True)

map_chart?=?multi_index_df.plot_animated(
????kind="bubble",
????filename="examples/example-bubble-chart.gif",
????x_data_label="Longitude",
????y_data_label="Latitude",
????size_data_label="Cases",
????color_data_label="Cases",
????vmax=5,?steps_per_period=3,?interpolate_period=True,?period_length=500,
????dpi=100
)

import?geopandas
import?pandas_alive
import?contextily

gdf?=?geopandas.read_file('data/nsw-covid19-cases-by-postcode.gpkg')
gdf.index?=?gdf.postcode
gdf?=?gdf.drop('postcode',axis=1)

result?=?gdf.iloc[:,?:20]
result['geometry']?=?gdf.iloc[:,?-1:]['geometry']

map_chart?=?result.plot_animated(filename='examples/example-geo-point-chart.gif',
?????????????????????????????????basemap_format={'source':contextily.providers.Stamen.Terrain})

import?geopandas
import?pandas_alive
import?contextily

gdf?=?geopandas.read_file('data/italy-covid-region.gpkg')
gdf.index?=?gdf.region
gdf?=?gdf.drop('region',axis=1)

result?=?gdf.iloc[:,?:20]
result['geometry']?=?gdf.iloc[:,?-1:]['geometry']

map_chart?=?result.plot_animated(filename='examples/example-geo-polygon-chart.gif',
?????????????????????????????????basemap_format={'source':?contextily.providers.Stamen.Terrain})

covid_df?=?pd.read_csv('data/covid19.csv',?index_col=0,?parse_dates=[0])

animated_line_chart?=?covid_df.diff().fillna(0).plot_animated(kind='line',?period_label=False,add_legend=False)
animated_bar_chart?=?covid_df.plot_animated(n_visible=10)

pandas_alive.animate_multiple_plots('examples/example-bar-and-line-chart.gif',
????????????????????????????????????[animated_bar_chart,?animated_line_chart],?enable_progress_bar=True)

def?population():
????urban_df?=?pd.read_csv("data/urban_pop.csv",?index_col=0,?parse_dates=[0])

????animated_line_chart?=?(
????????urban_df.sum(axis=1)
????????????.pct_change()
????????????.fillna(method='bfill')
????????????.mul(100)
????????????.plot_animated(kind="line",?title="Total?%?Change?in?Population",?period_label=False,?add_legend=False)
????)

????animated_bar_chart?=?urban_df.plot_animated(n_visible=10,?title='Top?10?Populous?Countries',?period_fmt="%Y")

????pandas_alive.animate_multiple_plots('examples/example-bar-and-line-urban-chart.gif',
????????????????????????????????????????[animated_bar_chart,?animated_line_chart],
????????????????????????????????????????title='Urban?Population?1977?-?2018',?adjust_subplot_top=0.85,
????????????????????????????????????????enable_progress_bar=True)

def?life():
????data_raw?=?pd.read_csv("data/long.csv")

????list_G7?=?[
????????"Canada",
????????"France",
????????"Germany",
????????"Italy",
????????"Japan",
????????"United?Kingdom",
????????"United?States",
????]

????data_raw?=?data_raw.pivot(
????????index="Year",?columns="Entity",?values="Life?expectancy?(Gapminder,?UN)"
????)

????data?=?pd.DataFrame()
????data["Year"]?=?data_raw.reset_index()["Year"]
????for?country?in?list_G7:
????????data[country]?=?data_raw[country].values

????data?=?data.fillna(method="pad")
????data?=?data.fillna(0)
????data?=?data.set_index("Year").loc[1900:].reset_index()

????data["Year"]?=?pd.to_datetime(data.reset_index()["Year"].astype(str))

????data?=?data.set_index("Year")
????data?=?data.iloc[:25,?:]

????animated_bar_chart?=?data.plot_animated(
????????period_fmt="%Y",?perpendicular_bar_func="mean",?period_length=200,?fixed_max=True
????)

????animated_line_chart?=?data.plot_animated(
????????kind="line",?period_fmt="%Y",?period_length=200,?fixed_max=True
????)

????pandas_alive.animate_multiple_plots(
????????"examples/life-expectancy.gif",
????????plots=[animated_bar_chart,?animated_line_chart],
????????title="Life?expectancy?in?G7?countries?up?to?2015",
????????adjust_subplot_left=0.2,?adjust_subplot_top=0.9,?enable_progress_bar=True
????)

def?nsw():
????import?geopandas
????import?pandas?as?pd
????import?pandas_alive
????import?contextily
????import?matplotlib.pyplot?as?plt
????import?json

????with?open('data/package_show.json',?'r',?encoding='utf8')as?fp:
????????data?=?json.load(fp)

????#?Extract?url?to?csv?component
????covid_nsw_data_url?=?data["result"]["resources"][0]["url"]
????print(covid_nsw_data_url)

????#?Read?csv?from?data?API?url
????nsw_covid?=?pd.read_csv('data/confirmed_cases_table1_location.csv')
????postcode_dataset?=?pd.read_csv("data/postcode-data.csv")

????#?Prepare?data?from?NSW?health?dataset

????nsw_covid?=?nsw_covid.fillna(9999)
????nsw_covid["postcode"]?=?nsw_covid["postcode"].astype(int)

????grouped_df?=?nsw_covid.groupby(["notification_date",?"postcode"]).size()
????grouped_df?=?pd.DataFrame(grouped_df).unstack()
????grouped_df.columns?=?grouped_df.columns.droplevel().astype(str)

????grouped_df?=?grouped_df.fillna(0)
????grouped_df.index?=?pd.to_datetime(grouped_df.index)

????cases_df?=?grouped_df

????#?Clean?data?in?postcode?dataset?prior?to?matching

????grouped_df?=?grouped_df.T
????postcode_dataset?=?postcode_dataset[postcode_dataset['Longitude'].notna()]
????postcode_dataset?=?postcode_dataset[postcode_dataset['Longitude']?!=?0]
????postcode_dataset?=?postcode_dataset[postcode_dataset['Latitude'].notna()]
????postcode_dataset?=?postcode_dataset[postcode_dataset['Latitude']?!=?0]
????postcode_dataset['Postcode']?=?postcode_dataset['Postcode'].astype(str)

????#?Build?GeoDataFrame?from?Lat?Long?dataset?and?make?map?chart
????grouped_df['Longitude']?=?grouped_df.index.map(postcode_dataset.set_index('Postcode')['Longitude'].to_dict())
????grouped_df['Latitude']?=?grouped_df.index.map(postcode_dataset.set_index('Postcode')['Latitude'].to_dict())
????gdf?=?geopandas.GeoDataFrame(
????????grouped_df,?geometry=geopandas.points_from_xy(grouped_df.Longitude,?grouped_df.Latitude),?crs="EPSG:4326")
????gdf?=?gdf.dropna()

????#?Prepare?GeoDataFrame?for?writing?to?geopackage
????gdf?=?gdf.drop(['Longitude',?'Latitude'],?axis=1)
????gdf.columns?=?gdf.columns.astype(str)
????gdf['postcode']?=?gdf.index
????#?gdf.to_file("data/nsw-covid19-cases-by-postcode.gpkg",?layer='nsw-postcode-covid',?driver="GPKG")

????#?Prepare?GeoDataFrame?for?plotting
????gdf.index?=?gdf.postcode
????gdf?=?gdf.drop('postcode',?axis=1)
????gdf?=?gdf.to_crs("EPSG:3857")??#?Web?Mercator

????result?=?gdf.iloc[:,?:22]
????result['geometry']?=?gdf.iloc[:,?-1:]['geometry']
????gdf?=?result

????map_chart?=?gdf.plot_animated(basemap_format={'source':?contextily.providers.Stamen.Terrain},?cmap='cool')

????#?cases_df.to_csv('data/nsw-covid-cases-by-postcode.csv')
????cases_df?=?cases_df.iloc[:22,?:]

????from?datetime?import?datetime

????bar_chart?=?cases_df.sum(axis=1).plot_animated(
????????kind='line',
????????label_events={
????????????'Ruby?Princess?Disembark':?datetime.strptime("19/03/2020",?"%d/%m/%Y"),
????????????#?'Lockdown':?datetime.strptime("31/03/2020",?"%d/%m/%Y")
????????},
????????fill_under_line_color="blue",
????????add_legend=False
????)

????map_chart.ax.set_title('Cases?by?Location')

????grouped_df?=?pd.read_csv('data/nsw-covid-cases-by-postcode.csv',?index_col=0,?parse_dates=[0])
????grouped_df?=?grouped_df.iloc[:22,?:]

????line_chart?=?(
????????grouped_df.sum(axis=1)
????????????.cumsum()
????????????.fillna(0)
????????????.plot_animated(kind="line",?period_label=False,?title="Cumulative?Total?Cases",?add_legend=False)
????)

????def?current_total(values):
????????total?=?values.sum()
????????s?=?f'Total?:?{int(total)}'
????????return?{'x':?.85,?'y':?.2,?'s':?s,?'ha':?'right',?'size':?11}

????race_chart?=?grouped_df.cumsum().plot_animated(
????????n_visible=5,?title="Cases?by?Postcode",?period_label=False,?period_summary_func=current_total
????)

????import?time

????timestr?=?time.strftime("%d/%m/%Y")

????plots?=?[bar_chart,?line_chart,?map_chart,?race_chart]

????from?matplotlib?import?rcParams

????rcParams.update({"figure.autolayout":?False})
????#?make?sure?figures?are?`Figure()`?instances
????figs?=?plt.Figure()
????gs?=?figs.add_gridspec(2,?3,?hspace=0.5)
????f3_ax1?=?figs.add_subplot(gs[0,?:])
????f3_ax1.set_title(bar_chart.title)
????bar_chart.ax?=?f3_ax1

????f3_ax2?=?figs.add_subplot(gs[1,?0])
????f3_ax2.set_title(line_chart.title)
????line_chart.ax?=?f3_ax2

????f3_ax3?=?figs.add_subplot(gs[1,?1])
????f3_ax3.set_title(map_chart.title)
????map_chart.ax?=?f3_ax3

????f3_ax4?=?figs.add_subplot(gs[1,?2])
????f3_ax4.set_title(race_chart.title)
????race_chart.ax?=?f3_ax4

????timestr?=?cases_df.index.max().strftime("%d/%m/%Y")
????figs.suptitle(f"NSW?COVID-19?Confirmed?Cases?up?to?{timestr}")

????pandas_alive.animate_multiple_plots(
????????'examples/nsw-covid.gif',
????????plots,
????????figs,
????????enable_progress_bar=True
????)

def?italy():
????import?geopandas
????import?pandas?as?pd
????import?pandas_alive
????import?contextily
????import?matplotlib.pyplot?as?plt

????region_gdf?=?geopandas.read_file('data/geo-data/italy-with-regions')
????region_gdf.NOME_REG?=?region_gdf.NOME_REG.str.lower().str.title()
????region_gdf?=?region_gdf.replace('Trentino-Alto?Adige/Sudtirol',?'Trentino-Alto?Adige')
????region_gdf?=?region_gdf.replace("Valle?D'Aosta/Vall??e?D'Aoste\r\nValle?D'Aosta/Vall??e?D'Aoste",?"Valle?d'Aosta")

????italy_df?=?pd.read_csv('data/Regional?Data?-?Sheet1.csv',?index_col=0,?header=1,?parse_dates=[0])

????italy_df?=?italy_df[italy_df['Region']?!=?'NA']

????cases_df?=?italy_df.iloc[:,?:3]
????cases_df['Date']?=?cases_df.index
????pivoted?=?cases_df.pivot(values='New?positives',?index='Date',?columns='Region')
????pivoted.columns?=?pivoted.columns.astype(str)
????pivoted?=?pivoted.rename(columns={'nan':?'Unknown?Region'})

????cases_gdf?=?pivoted.T
????cases_gdf['geometry']?=?cases_gdf.index.map(region_gdf.set_index('NOME_REG')['geometry'].to_dict())

????cases_gdf?=?cases_gdf[cases_gdf['geometry'].notna()]

????cases_gdf?=?geopandas.GeoDataFrame(cases_gdf,?crs=region_gdf.crs,?geometry=cases_gdf.geometry)

????gdf?=?cases_gdf

????result?=?gdf.iloc[:,?:22]
????result['geometry']?=?gdf.iloc[:,?-1:]['geometry']
????gdf?=?result

????map_chart?=?gdf.plot_animated(basemap_format={'source':?contextily.providers.Stamen.Terrain},?cmap='viridis')

????cases_df?=?pivoted
????cases_df?=?cases_df.iloc[:22,?:]

????from?datetime?import?datetime

????bar_chart?=?cases_df.sum(axis=1).plot_animated(
????????kind='line',
????????label_events={
????????????'Schools?Close':?datetime.strptime("4/03/2020",?"%d/%m/%Y"),
????????????'Phase?I?Lockdown':?datetime.strptime("11/03/2020",?"%d/%m/%Y"),
????????????#?'1M?Global?Cases':?datetime.strptime("02/04/2020",?"%d/%m/%Y"),
????????????#?'100k?Global?Deaths':?datetime.strptime("10/04/2020",?"%d/%m/%Y"),
????????????#?'Manufacturing?Reopens':?datetime.strptime("26/04/2020",?"%d/%m/%Y"),
????????????#?'Phase?II?Lockdown':?datetime.strptime("4/05/2020",?"%d/%m/%Y"),
????????},
????????fill_under_line_color="blue",
????????add_legend=False
????)

????map_chart.ax.set_title('Cases?by?Location')

????line_chart?=?(
????????cases_df.sum(axis=1)
????????????.cumsum()
????????????.fillna(0)
????????????.plot_animated(kind="line",?period_label=False,?title="Cumulative?Total?Cases",?add_legend=False)
????)

????def?current_total(values):
????????total?=?values.sum()
????????s?=?f'Total?:?{int(total)}'
????????return?{'x':?.85,?'y':?.1,?'s':?s,?'ha':?'right',?'size':?11}

????race_chart?=?cases_df.cumsum().plot_animated(
????????n_visible=5,?title="Cases?by?Region",?period_label=False,?period_summary_func=current_total
????)

????import?time

????timestr?=?time.strftime("%d/%m/%Y")

????plots?=?[bar_chart,?race_chart,?map_chart,?line_chart]

????#?Otherwise?titles?overlap?and?adjust_subplot?does?nothing
????from?matplotlib?import?rcParams
????from?matplotlib.animation?import?FuncAnimation

????rcParams.update({"figure.autolayout":?False})
????#?make?sure?figures?are?`Figure()`?instances
????figs?=?plt.Figure()
????gs?=?figs.add_gridspec(2,?3,?hspace=0.5)
????f3_ax1?=?figs.add_subplot(gs[0,?:])
????f3_ax1.set_title(bar_chart.title)
????bar_chart.ax?=?f3_ax1

????f3_ax2?=?figs.add_subplot(gs[1,?0])
????f3_ax2.set_title(race_chart.title)
????race_chart.ax?=?f3_ax2

????f3_ax3?=?figs.add_subplot(gs[1,?1])
????f3_ax3.set_title(map_chart.title)
????map_chart.ax?=?f3_ax3

????f3_ax4?=?figs.add_subplot(gs[1,?2])
????f3_ax4.set_title(line_chart.title)
????line_chart.ax?=?f3_ax4

????axes?=?[f3_ax1,?f3_ax2,?f3_ax3,?f3_ax4]
????timestr?=?cases_df.index.max().strftime("%d/%m/%Y")
????figs.suptitle(f"Italy?COVID-19?Confirmed?Cases?up?to?{timestr}")

????pandas_alive.animate_multiple_plots(
????????'examples/italy-covid.gif',
????????plots,
????????figs,
????????enable_progress_bar=True
????)

def?simple():
????import?pandas?as?pd
????import?matplotlib.pyplot?as?plt
????import?pandas_alive
????import?numpy?as?np

????#?Physical?constants
????g?=?9.81
????L?=?.4
????mu?=?0.2

????THETA_0?=?np.pi?*?70?/?180??#?init?angle?=?70degs
????THETA_DOT_0?=?0??#?no?init?angVel
????DELTA_T?=?0.01??#?time?stepping
????T?=?1.5??#?time?period

????#?Definition?of?ODE?(ordinary?differential?equation)
????def?get_theta_double_dot(theta,?theta_dot):
????????return?-mu?*?theta_dot?-?(g?/?L)?*?np.sin(theta)

????#?Solution?to?the?differential?equation
????def?pendulum(t):
????????#?initialise?changing?values
????????theta?=?THETA_0
????????theta_dot?=?THETA_DOT_0
????????delta_t?=?DELTA_T
????????ang?=?[]
????????ang_vel?=?[]
????????ang_acc?=?[]
????????times?=?[]
????????for?time?in?np.arange(0,?t,?delta_t):
????????????theta_double_dot?=?get_theta_double_dot(
????????????????theta,?theta_dot
????????????)
????????????theta?+=?theta_dot?*?delta_t
????????????theta_dot?+=?theta_double_dot?*?delta_t
????????????times.append(time)
????????????ang.append(theta)
????????????ang_vel.append(theta_dot)
????????????ang_acc.append(theta_double_dot)
????????data?=?np.array([ang,?ang_vel,?ang_acc])
????????return?pd.DataFrame(data=data.T,?index=np.array(times),?columns=["angle",?"ang_vel",?"ang_acc"])

????#?units?used?for?ref:?["angle?[rad]",?"ang_vel?[rad/s]",?"ang_acc?[rad/s^2]"]
????df?=?pendulum(T)
????df.index.names?=?["Time?(s)"]
????print(df)

????#?generate?dataFrame?for?animated?bubble?plot
????df2?=?pd.DataFrame(index=df.index)
????df2["dx?(m)"]?=?L?*?np.sin(df["angle"])
????df2["dy?(m)"]?=?-L?*?np.cos(df["angle"])
????df2["ang_vel"]?=?abs(df["ang_vel"])
????df2["size"]?=?df2["ang_vel"]?*?100??#?scale?angular?vels?to?get?nice?size?on?bubble?plot
????print(df2)

????#?static?pandas?plots
????#
????#?print(plt.style.available)
????#?NOTE:?2?lines?below?required?in?Jupyter?to?switch?styles?correctly
????plt.rcParams.update(plt.rcParamsDefault)
????plt.style.use("ggplot")??#?set?plot?style

????fig,?(ax1a,?ax2b)?=?plt.subplots(1,?2,?figsize=(8,?4),?dpi=100)??#?1?row,?2?subplots
????#?fig.subplots_adjust(wspace=0.1)??????#?space?subplots?in?row
????fig.set_tight_layout(True)
????fontsize?=?"small"

????df.plot(ax=ax1a).legend(fontsize=fontsize)
????ax1a.set_title("Outputs?vs?Time",?fontsize="medium")
????ax1a.set_xlabel('Time?[s]',?fontsize=fontsize)
????ax1a.set_ylabel('Amplitudes',?fontsize=fontsize);

????df.plot(ax=ax2b,?x="angle",?y=["ang_vel",?"ang_acc"]).legend(fontsize=fontsize)
????ax2b.set_title("Outputs?vs?Angle?|?Phase-Space",?fontsize="medium")
????ax2b.set_xlabel('Angle?[rad]',?fontsize=fontsize)
????ax2b.set_ylabel('Angular?Velocity?/?Acc',?fontsize=fontsize)

????#?sample?scatter?plot?with?colorbar
????fig,?ax?=?plt.subplots()
????sc?=?ax.scatter(df2["dx?(m)"],?df2["dy?(m)"],?s=df2["size"]?*?.1,?c=df2["ang_vel"],?cmap="jet")
????cbar?=?fig.colorbar(sc)
????cbar.set_label(label="ang_vel?[rad/s]",?fontsize="small")
????#?sc.set_clim(350,?400)
????ax.tick_params(labelrotation=0,?labelsize="medium")
????ax_scale?=?1.
????ax.set_xlim(-L?*?ax_scale,?L?*?ax_scale)
????ax.set_ylim(-L?*?ax_scale?-?0.1,?L?*?ax_scale?-?0.1)
????#?make?axes?square:?a?circle?shows?as?a?circle
????ax.set_aspect(1?/?ax.get_data_ratio())
????ax.arrow(0,?0,?df2["dx?(m)"].iloc[-1],?df2["dy?(m)"].iloc[-1],
?????????????color="dimgray",?ls=":",?lw=2.5,?width=.0,?head_width=0,?zorder=-1
?????????????)
????ax.text(0,?0.15,?s="size?and?colour?of?pendulum?bob\nbased?on?pd?column\nfor?angular?velocity",
????????????ha='center',?va='center')

????#?plt.show()

????dpi?=?100
????ax_scale?=?1.1
????figsize?=?(3,?3)
????fontsize?=?"small"

????#?set?up?figure?to?pass?onto?`pandas_alive`
????#?NOTE:?by?using?Figure?(capital?F)?instead?of?figure()?`FuncAnimation`?seems?to?run?twice?as?fast!
????#?fig1,?ax1?=?plt.subplots()
????fig1?=?plt.Figure()
????ax1?=?fig1.add_subplot()
????fig1.set_size_inches(figsize)
????ax1.set_title("Simple?pendulum?animation,?L="?+?str(L)?+?"m",?fontsize="medium")
????ax1.set_xlabel("Time?(s)",?color='dimgray',?fontsize=fontsize)
????ax1.set_ylabel("Amplitudes",?color='dimgray',?fontsize=fontsize)
????ax1.tick_params(labelsize=fontsize)

????#?pandas_alive
????line_chart?=?df.plot_animated(filename="pend-line.gif",?kind='line',?period_label={'x':?0.05,?'y':?0.9},
??????????????????????????????????steps_per_period=1,?interpolate_period=False,?period_length=50,
??????????????????????????????????period_fmt='Time:{x:10.2f}',
??????????????????????????????????enable_progress_bar=True,?fixed_max=True,?dpi=100,?fig=fig1
??????????????????????????????????)
????plt.close()

????#?Video('examples/pend-line.mp4',?html_attributes="controls?muted?autoplay")

????#?set?up?and?generate?animated?scatter?plot
????#

????#?set?up?figure?to?pass?onto?`pandas_alive`
????#?NOTE:?by?using?Figure?(capital?F)?instead?of?figure()?`FuncAnimation`?seems?to?run?twice?as?fast!
????fig1sc?=?plt.Figure()
????ax1sc?=?fig1sc.add_subplot()
????fig1sc.set_size_inches(figsize)
????ax1sc.set_title("Simple?pendulum?animation,?L="?+?str(L)?+?"m",?fontsize="medium")
????ax1sc.set_xlabel("Time?(s)",?color='dimgray',?fontsize=fontsize)
????ax1sc.set_ylabel("Amplitudes",?color='dimgray',?fontsize=fontsize)
????ax1sc.tick_params(labelsize=fontsize)

????#?pandas_alive
????scatter_chart?=?df.plot_animated(filename="pend-scatter.gif",?kind='scatter',?period_label={'x':?0.05,?'y':?0.9},
?????????????????????????????????????steps_per_period=1,?interpolate_period=False,?period_length=50,
?????????????????????????????????????period_fmt='Time:{x:10.2f}',
?????????????????????????????????????enable_progress_bar=True,?fixed_max=True,?dpi=100,?fig=fig1sc,?size="ang_vel"
?????????????????????????????????????)
????plt.close()

????print("Points?size?follows?one?of?the?pd?columns:?ang_vel")
????#?Video('./pend-scatter.gif',?html_attributes="controls?muted?autoplay")

????#?set?up?and?generate?animated?bar?race?chart
????#
????#?set?up?figure?to?pass?onto?`pandas_alive`
????#?NOTE:?by?using?Figure?(capital?F)?instead?of?figure()?`FuncAnimation`?seems?to?run?twice?as?fast!
????fig2?=?plt.Figure()
????ax2?=?fig2.add_subplot()
????fig2.set_size_inches(figsize)
????ax2.set_title("Simple?pendulum?animation,?L="?+?str(L)?+?"m",?fontsize="medium")
????ax2.set_xlabel("Amplitudes",?color='dimgray',?fontsize=fontsize)
????ax2.set_ylabel("",?color='dimgray',?fontsize="x-small")
????ax2.tick_params(labelsize=fontsize)

????#?pandas_alive
????race_chart?=?df.plot_animated(filename="pend-race.gif",?kind='race',?period_label={'x':?0.05,?'y':?0.9},
??????????????????????????????????steps_per_period=1,?interpolate_period=False,?period_length=50,
??????????????????????????????????period_fmt='Time:{x:10.2f}',
??????????????????????????????????enable_progress_bar=True,?fixed_max=False,?dpi=100,?fig=fig2
??????????????????????????????????)
????plt.close()

????#?set?up?and?generate?bubble?animated?plot
????#

????#?set?up?figure?to?pass?onto?`pandas_alive`
????#?NOTE:?by?using?Figure?(capital?F)?instead?of?figure()?`FuncAnimation`?seems?to?run?twice?as?fast!
????fig3?=?plt.Figure()
????ax3?=?fig3.add_subplot()
????fig3.set_size_inches(figsize)
????ax3.set_title("Simple?pendulum?animation,?L="?+?str(L)?+?"m",?fontsize="medium")
????ax3.set_xlabel("Hor?Displacement?(m)",?color='dimgray',?fontsize=fontsize)
????ax3.set_ylabel("Ver?Displacement?(m)",?color='dimgray',?fontsize=fontsize)
????#?limits?&?ratio?below?get?the?graph?square
????ax3.set_xlim(-L?*?ax_scale,?L?*?ax_scale)
????ax3.set_ylim(-L?*?ax_scale?-?0.1,?L?*?ax_scale?-?0.1)
????ratio?=?1.??#?this?is?visual?ratio?of?axes
????ax3.set_aspect(ratio?/?ax3.get_data_ratio())

????ax3.arrow(0,?0,?df2["dx?(m)"].iloc[-1],?df2["dy?(m)"].iloc[-1],
??????????????color="dimgray",?ls=":",?lw=1,?width=.0,?head_width=0,?zorder=-1)

????#?pandas_alive
????bubble_chart?=?df2.plot_animated(
????????kind="bubble",?filename="pend-bubble.gif",
????????x_data_label="dx?(m)",?y_data_label="dy?(m)",
????????size_data_label="size",?color_data_label="ang_vel",?cmap="jet",
????????period_label={'x':?0.05,?'y':?0.9},?vmin=None,?vmax=None,
????????steps_per_period=1,?interpolate_period=False,?period_length=50,?period_fmt='Time:{x:10.2f}s',
????????enable_progress_bar=True,?fixed_max=False,?dpi=dpi,?fig=fig3
????)
????plt.close()

????print("Bubble?size?&?colour?animates?with?pd?data?column?for?ang_vel.")

????#?Combined?plots
????#
????fontsize?=?"x-small"
????#?Otherwise?titles?overlap?and?subplots_adjust?does?nothing
????from?matplotlib?import?rcParams
????rcParams.update({"figure.autolayout":?False})

????figs?=?plt.Figure(figsize=(9,?4),?dpi=100)
????figs.subplots_adjust(wspace=0.1)
????gs?=?figs.add_gridspec(2,?2)

????ax1?=?figs.add_subplot(gs[0,?0])
????ax1.set_xlabel("Time(s)",?color='dimgray',?fontsize=fontsize)
????ax1.set_ylabel("Amplitudes",?color='dimgray',?fontsize=fontsize)
????ax1.tick_params(labelsize=fontsize)

????ax2?=?figs.add_subplot(gs[1,?0])
????ax2.set_xlabel("Amplitudes",?color='dimgray',?fontsize=fontsize)
????ax2.set_ylabel("",?color='dimgray',?fontsize=fontsize)
????ax2.tick_params(labelsize=fontsize)

????ax3?=?figs.add_subplot(gs[:,?1])
????ax3.set_xlabel("Hor?Displacement?(m)",?color='dimgray',?fontsize=fontsize)
????ax3.set_ylabel("Ver?Displacement?(m)",?color='dimgray',?fontsize=fontsize)
????ax3.tick_params(labelsize=fontsize)
????#?limits?&?ratio?below?get?the?graph?square
????ax3.set_xlim(-L?*?ax_scale,?L?*?ax_scale)
????ax3.set_ylim(-L?*?ax_scale?-?0.1,?L?*?ax_scale?-?0.1)
????ratio?=?1.??#?this?is?visual?ratio?of?axes
????ax3.set_aspect(ratio?/?ax3.get_data_ratio())

????line_chart.ax?=?ax1
????race_chart.ax?=?ax2
????bubble_chart.ax?=?ax3

????plots?=?[line_chart,?race_chart,?bubble_chart]
????#?pandas_alive?combined?using?custom?figure
????pandas_alive.animate_multiple_plots(
????????filename='pend-combined.gif',?plots=plots,?custom_fig=figs,?dpi=100,?enable_progress_bar=True,
????????adjust_subplot_left=0.2,?adjust_subplot_right=None,
????????title="Simple?pendulum?animations,?L="?+?str(L)?+?"m",?title_fontsize="medium"
????)
????plt.close()

#?中文顯示
plt.rcParams['font.sans-serif']?=?['SimHei']??#?Windows
plt.rcParams['font.sans-serif']?=?['Hiragino?Sans?GB']?#?Mac
plt.rcParams['axes.unicode_minus']?=?False

#?讀取數據
df_result?=?pd.read_csv('data/yuhuanshui.csv',?index_col=0,?parse_dates=[0])
#?生成圖表
animated_line_chart?=?df_result.diff().fillna(0).plot_animated(kind='line',?period_label=False,?add_legend=False)
animated_bar_chart?=?df_result.plot_animated(n_visible=10)
pandas_alive.animate_multiple_plots('examples/yuhuanshui.gif',
????????????????????????????????????[animated_bar_chart,?animated_line_chart],?enable_progress_bar=True,
????????????????????????????????????title='我是余歡水演職人員熱度排行')