How to draw a chart with Python matplotlib plotly
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I. collate the data
Using 300 movies as data source
Import pandas as pd cnboo=pd.read_excel ("cnboNPPD1.xls") cnboo
Import seaborn as snsimport numpy as np import matplotlib as mplfrom matplotlib import pyplot as plt import pandas as pd from datetime import datetime,timedelta%matplotlib inlineplt.rcParams ['font.sans-serif'] = [' SimHei'] # is used to display the Chinese label plt.rcParams ['axes.unicode_minus'] = False # to display the negative sign from datetime import datetime! Pip install plotly # install import matplotlib.pyplot as pltimport plotlyfrom plotly.offline import download_plotlyjs,init_notebook_mode,plot,iplotx=cnboo ['BO'] .tolist () y=cnboo [' PERSONS'] .tolist () dict01= {"x": X, "y": y} dict01 II, line chart # line chart iplot ([dict01])
3. Scatter plot import plotly.graph_objs as goiplot ([go.Scatter (Xerox recording yearly recording markers'))
# randomly generated dot graph import numpy as npiplot ([go.Scatter (x=np.random.randn), y=np.random.randn (100), mode='markers')] go
Trace=go.Scatter (x=cnboo ['PRICE'],) data= [trace] iplot (data)
Trace=go.Scatter (x=cnboo ['PRICE'], data= [trace] iplot (data)
Pie chart colors= ['# dc2624','#2b4750','#45a0a2','#e87a59','#7dcaa9','#649E7D','#dc8018','# C89F91', '6c6d6c',' 4f6268', 'filmtype=cnboo [' TYPE'] filmbo=cnboo ['PRICE'] trace=go.Pie (labels=filmtype,values=filmbo, hoverinfo='label+percent',textinfo='value',textfont=dict (size=10), marker=dict (color='#000000') Width=3)) data= [trace] iplot (data)
Filmtype=cnboo ['TYPE'] filmbo=cnboo [' PRICE'] trace=go.Pie (labels=filmtype,values=filmbo, hoverinfo='label+percent',textinfo='value',textfont=dict (size=12), marker=dict (colors=colors)) data= [trace] iplot (data)
Bar chart # plotly bartrace1=go.Bar (x=cnboo ['TYPE'], y=cnboo [' PRICE'], name= "types and fares") trace2=go.Bar (x=cnboo ['TYPE'], yearly TYPE' name = "Type and number of people") layout=go.Layout (title= "relationship between Chinese Film types and ticket prices, number of people", xaxis=dict (title=' Film genre')) data= [trace1,trace2] fig=go.Figure (data,layout=layout) iplot (fig)
Dot map (setting multiple go objects) trace1=go.Scatter (x=cnboo ['TYPE'], y=cnboo [' PRICE'], name= "Type and fare", mode= "markers", marker=dict (color= "red", size=8)) trace2=go.Scatter (x=cnboo ['TYPE'], y=cnboo [' PERSONS'], name= "Type and number", mode= "markers", marker=dict (color= "blue", size=5)) data= [trace1,trace2] iplot (data)
Trace1=go.Scatter (x=cnboo ['TYPE'], y=cnboo [' PRICE'], name= "genres and fares", mode= "markers", marker=dict (color= "red", size=8)) trace2=go.Scatter (x=cnboo ['TYPE'], y=cnboo [' PERSONS'], name= "genres and people", mode= "markers", marker=dict (color= "blue", size=5) layout=go.Layout (title= "Chinese Movie genres and fares" Number of people ", plot_bgcolor=" # FFFFFF ") data= [trace1,trace2] fig=go.Figure (data,layout=layout) iplot (fig)
7. 2D density map import plotly.figure_factory as fffig=ff.create_2d_density (fig,filename=' score and person-time') iplot (fig,filename=' score and person-time)
Colorscale= ['rgb (20,38,220)', 'rgb (255,255,255)'] # the last color is the calling background fig=ff.create_2d_density (fig,filename=' score and person-times')
8. Simple 3D map layout=go.Layout (title= "relationship between Chinese box office and ticket prices", barmode= "group") trace01=go.Scatter3d (x=cnboo ['BO'], y=cnboo [' PRICE'], z=cnboo ['PERSONS'], mode='markers', marker=dict (size=12,color=colors,colorscale='Viridis', opacity=0.5,showscale=True) # opacity is transparency) data= [Trace01] fig=go.Figure (data=data,layout=layout) iplot (fig,filename='3d')
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