Python繪制數(shù)據(jù)動態(tài)圖的方法詳解

更新時間：2022年07月05日 10:00:28 作者：pythonic生物人

這篇文章主要為大家詳細(xì)介紹了如何利用Python語言繪制好看的數(shù)據(jù)動態(tài)圖，文中的示例代碼講解詳細(xì)，感興趣的小伙伴可以跟隨小編一起動手嘗試一下

安裝

pip?install?pandas_alive

#或者
conda?install?pandas_alive?-c?conda-forge

玩起來

支持?jǐn)?shù)據(jù)

數(shù)據(jù)格式如下，

使用方法類似pandas??這些，pandas僅需一行代碼解決支持圖形類別

動態(tài)地圖

結(jié)合geopandas，

動態(tài)水平bar

import?pandas?as?pd
import?pandas_alive
import?matplotlib.pyplot?as?plt

plt.style.use('ggplot')

#讀入數(shù)據(jù)
elec_df?=?pd.read_csv("Aus_Elec_Gen_1980_2018.csv",
??????????????????????index_col=0,
??????????????????????parse_dates=[0],
??????????????????????thousands=',')

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


#缺省值0填充、繪圖
elec_df.fillna(0).tail(n=10).plot_animated(
????'electricity-generated-australia.gif',??#保存gif名稱
????period_fmt="%d/%m/%Y",??#動態(tài)更新圖中時間戳
????title='Australian?Electricity?Sources?1980-2018',??#標(biāo)題
????perpendicular_bar_func='mean',??#添加均值輔助線
????period_summary_func=current_total,??#匯總
????cmap='Set1',??#定義調(diào)色盤
????n_visible=5,??#柱子顯示數(shù)
????orientation='h',#柱子方向
)

動態(tài)垂直bar

動態(tài)折線

elec_df.diff().fillna(0).tail(n=10).plot_animated(filename='line-chart.gif',
?????????????????????????????????????????????????kind='line',#指定折線模式
?????????????????????????????????????????????????cmap='Set1',
?????????????????????????????????????????????????period_label={
?????????????????????????????????????????????????????'x':?0.25,
?????????????????????????????????????????????????????'y':?0.9
?????????????????????????????????????????????????},
?????????????????????????????????????????????????line_width=1,
?????????????????????????????????????????????????add_legend=True,
?????????????????????????????????????????????????fill_under_line_color='#01a2d9')

動態(tài)累積bar

import?pandas_alive
covid_df.sum(axis=1).fillna(0).tail(n=10).plot_animated(
????filename='sumbar-chart.gif',
????kind='bar',???#指定bar模式
????cmap='Set1',??#定義調(diào)色盤
????period_label={
????????'x':?0.1,
????????'y':?0.9
????},
????orientation='h',
????enable_progress_bar=True,
????steps_per_period=2,
????interpolate_period=True,
????period_length=200)

動態(tài)散點圖

import?pandas?as?pd
import?pandas_alive

#max散點數(shù)據(jù)
max_temp_df?=?pd.read_csv(
????"Newcastle_Australia_Max_Temps.csv",
????parse_dates={"Timestamp":?["Year",?"Month",?"Day"]},
)

#min散點數(shù)據(jù)
min_temp_df?=?pd.read_csv(
????"Newcastle_Australia_Min_Temps.csv",
????parse_dates={"Timestamp":?["Year",?"Month",?"Day"]},
)

#按時間戳merge?max/min數(shù)據(jù)
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.head(n=5000)[keep_columns].resample("Y").mean().plot_animated(
????filename='scatter-chart.gif',
????cmap='Set1',?
????kind="scatter",#指定散點模式
????size=10,
????title='Max?&?Min?Temperature?Newcastle,?Australia')

動態(tài)氣泡圖

import?pandas_alive

multi_index_df?=?pd.read_csv("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.tail(n=40).plot_animated(
????kind="bubble",??#指定氣泡模式
????filename="bubble-chart.gif",
????x_data_label="Longitude",
????y_data_label="Latitude",
????size_data_label="Cases",
????color_data_label="Cases",
????vmax=5,
????steps_per_period=1,
????interpolate_period=True,
????period_length=500,
????dpi=150)