因此，让我们从代码中的问题开始。
您正在
from plotly.grid_objs import Grid, Column
用来制作图形，但这是在线绘图的功能，我已经用一个简单的数据框替换了您的逻辑网格，基本上完成了同样的事情。其次，我注意到该图形没有显示数据，经过分析，我最终发现您已将X轴的范围设置为
[30, 85]
，但X轴的值介于之间1-15k
。
请在下面找到我的更新代码。希望这能解决您的问题。
码：
import pandas as pdimport numpy as npfrom __future__ import divisionimport plotly.plotly as pyfrom plotly.offline import download_plotlyjs, init_notebook_mode, iplotfrom plotly.graph_objs import *init_notebook_mode()from plotly.grid_objs import Grid, Columnfrom plotly.tools import FigureFactory as FFdataset=pd.read_csv('god_mod_copia.csv')years_from_col = set(dataset['year'])years_ints = sorted(list(years_from_col))years = [str(year) for year in years_ints]# make list of continentscontinents = []for continent in dataset['continent']: if continent not in continents: continents.append(continent)df = pd.Dataframe()# make gridfor year in years: for continent in continents: dataset_by_year = dataset[dataset['year'] == int(year)] dataset_by_year_and_cont = dataset_by_year[dataset_by_year['continent'] == continent] for col_name in dataset_by_year_and_cont: # each column name is unique temp = '{year}+{continent}+{header}_grid'.format( year=year, continent=continent, header=col_name ) #if dataset_by_year_and_cont[col_name].size != 0: df = df.append({'value': list(dataset_by_year_and_cont[col_name]), 'key': temp}, ignore_index=True)figure = { 'data': [], 'layout': {}, 'frames': []}figure['layout']['xaxis'] = {'title': 'GDP per Capita', 'type': 'log', 'autorange': True} #was not set properlyfigure['layout']['yaxis'] = {'title': 'Life Expectancy', 'autorange': True} #was not set properlyfigure['layout']['hovermode'] = 'closest'figure['layout']['showlegend'] = Truefigure['layout']['sliders'] = { 'args': [ 'slider.value', { 'duration': 400, 'ease': 'cubic-in-out' } ], 'initialValue': '2007', 'plotlycommand': 'animate', 'values': years, 'visible': True}figure['layout']['updatemenus'] = [ { 'buttons': [ { 'args': [None, {'frame': {'duration': 500, 'redraw': False}, 'fromcurrent': True, 'transition': {'duration': 300, 'easing': 'quadratic-in-out'}}], 'label': 'Play', 'method': 'animate' }, { 'args': [[None], {'frame': {'duration': 0, 'redraw': False}, 'mode': 'immediate', 'transition': {'duration': 0}}], 'label': 'Pause', 'method': 'animate' } ], 'direction': 'left', 'pad': {'r': 10, 't': 87}, 'showactive': False, 'type': 'buttons', 'x': 0.1, 'xanchor': 'right', 'y': 0, 'yanchor': 'top' }]sliders_dict = { 'active': 0, 'yanchor': 'top', 'xanchor': 'left', 'currentvalue': { 'font': {'size': 20}, 'prefix': 'Year:', 'visible': True, 'xanchor': 'right' }, 'transition': {'duration': 300, 'easing': 'cubic-in-out'}, 'pad': {'b': 10, 't': 50}, 'len': 0.9, 'x': 0.1, 'y': 0, 'steps': []}custom_colors = { 'Asia': 'rgb(171, 99, 250)', 'Europe': 'rgb(230, 99, 250)', 'Africa': 'rgb(99, 110, 250)', 'Americas': 'rgb(25, 211, 243)', #'Oceania': 'rgb(9, 255, 255)' 'Oceania': 'rgb(50, 170, 255)'}col_name_template = '{year}+{continent}+{header}_grid'year = 2007for continent in continents: data_dict = { 'x': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='GDP_per_capita' ), 'value'].values[0], 'y': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='Life_satisfaction' ), 'value'].values[0], 'mode': 'markers', 'text': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='country' ), 'value'].values[0], 'marker': { 'sizemode': 'area', 'sizeref': 200000, 'size': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='Total_population' ), 'value'].values[0], 'color': custom_colors[continent] }, 'name': continent } figure['data'].append(data_dict)for year in years: frame = {'data': [], 'name': str(year)} for continent in continents: data_dict = { 'x': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='GDP_per_capita' ), 'value'].values[0], 'y': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='Life_satisfaction' ), 'value'].values[0], 'mode': 'markers', 'text': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='country' ), 'value'].values[0], 'marker': { 'sizemode': 'area', 'sizeref': 200000, 'size': df.loc[df['key']==col_name_template.format( year=year, continent=continent, header='Total_population' ), 'value'].values[0], 'color': custom_colors[continent] }, 'name': continent } frame['data'].append(data_dict) figure['frames'].append(frame) #this block was indented and should not have been. slider_step = {'args': [ [year], {'frame': {'duration': 300, 'redraw': False}, 'mode': 'immediate', 'transition': {'duration': 300}} ], 'label': year, 'method': 'animate'} sliders_dict['steps'].append(slider_step)figure['layout']['sliders'] = [sliders_dict]iplot(figure, config={'scrollzoom': True})
