我只是学习Plotly,我正在努力使我的python代码更好。这是我的数据框:
为了可视化,这是我的代码,但是我认为可以通过For循环来完成:
fig = go.Figure()
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,0], mode ='lines', name = 'Australian Capital Territory'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,1], mode ='lines', name = 'New South Wales'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,2], mode ='lines', name = 'Northern Territory'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,3], mode ='lines', name = 'Queensland'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,4], mode ='lines', name = 'South Australia'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,5], mode ='lines', name = 'Tasmania'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,6], mode ='lines', name = 'Victoria'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,7], mode ='lines', name = 'Western Australia'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,8], mode ='lines', name = 'New Zealand'))
annotations = []
annotations.append(dict(xref='paper', yref='paper', x=0.0, y=1.05,
xanchor='left', yanchor='bottom',
text="Covid 19 Death Cases between Australian' states vs New Zealand",
font=dict(family='Arial',
size=18,
color='rgb(37,37,37)'),
showarrow=False))
fig.update_layout(legend=dict(y=0.5, traceorder='reversed', font_size=16),
plot_bgcolor='white',
annotations=annotations,
xaxis_title="Date",
yaxis_title="Number of Death"
)
fig.show()
我正在为此部分使用For循环:
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,0], mode ='lines', name = 'Australian Capital Territory'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,1], mode ='lines', name = 'New South Wales'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,2], mode ='lines', name = 'Northern Territory'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,3], mode ='lines', name = 'Queensland'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,4], mode ='lines', name = 'South Australia'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,5], mode ='lines', name = 'Tasmania'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,6], mode ='lines', name = 'Victoria'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,7], mode ='lines', name = 'Western Australia'))
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,8], mode ='lines', name = 'New Zealand'))
关于如何使用For循环的任何想法,将不胜感激。这是来自Plotly的示例:
import plotly.graph_objects as go
import numpy as np
title = 'Main Source for News'
labels = ['Television', 'Newspaper', 'Internet', 'Radio']
colors = ['rgb(67,67,67)', 'rgb(115,115,115)', 'rgb(49,130,189)', 'rgb(189,189,189)']
mode_size = [8, 8, 12, 8]
line_size = [2, 2, 4, 2]
x_data = np.vstack((np.arange(2001, 2014),)*4)
y_data = np.array([
[74, 82, 80, 74, 73, 72, 74, 70, 70, 66, 66, 69],
[45, 42, 50, 46, 36, 36, 34, 35, 32, 31, 31, 28],
[13, 14, 20, 24, 20, 24, 24, 40, 35, 41, 43, 50],
[18, 21, 18, 21, 16, 14, 13, 18, 17, 16, 19, 23],
])
fig = go.Figure()
for i in range(0, 4):
fig.add_trace(go.Scatter(x=x_data[i], y=y_data[i], mode='lines',
name=labels[i],
line=dict(color=colors[i], width=line_size[i]),
connectgaps=True,
))
# endpoints
fig.add_trace(go.Scatter(
x=[x_data[i][0], x_data[i][-1]],
y=[y_data[i][0], y_data[i][-1]],
mode='markers',
marker=dict(color=colors[i], size=mode_size[i])
))
fig.update_layout(
xaxis=dict(
showline=True,
showgrid=False,
showticklabels=True,
linecolor='rgb(204, 204, 204)',
linewidth=2,
ticks='outside',
tickfont=dict(
family='Arial',
size=12,
color='rgb(82, 82, 82)',
),
),
yaxis=dict(
showgrid=False,
zeroline=False,
showline=False,
showticklabels=False,
),
autosize=False,
margin=dict(
autoexpand=False,
l=100,
r=20,
t=110,
),
showlegend=False,
plot_bgcolor='white'
)
annotations = []
# Adding labels
for y_trace, label, color in zip(y_data, labels, colors):
# labeling the left_side of the plot
annotations.append(dict(xref='paper', x=0.05, y=y_trace[0],
xanchor='right', yanchor='middle',
text=label + ' {}%'.format(y_trace[0]),
font=dict(family='Arial',
size=16),
showarrow=False))
# labeling the right_side of the plot
annotations.append(dict(xref='paper', x=0.95, y=y_trace[11],
xanchor='left', yanchor='middle',
text='{}%'.format(y_trace[11]),
font=dict(family='Arial',
size=16),
showarrow=False))
# Title
annotations.append(dict(xref='paper', yref='paper', x=0.0, y=1.05,
xanchor='left', yanchor='bottom',
text='Main Source for News',
font=dict(family='Arial',
size=30,
color='rgb(37,37,37)'),
showarrow=False))
# Source
annotations.append(dict(xref='paper', yref='paper', x=0.5, y=-0.1,
xanchor='center', yanchor='top',
text='Source: PewResearch Center & ' +
'Storytelling with data',
font=dict(family='Arial',
size=12,
color='rgb(150,150,150)'),
showarrow=False))
fig.update_layout(annotations=annotations)
fig.show()
这里是您要在for
循环中创建所有迹线的行:
for idx, col in enumerate(anz_d_df.columns, 0):
fig.add_trace(go.Scatter(x = anz_d_df.index , y = anz_d_df.iloc[:,idx], mode ='lines', name = col))
此循环使用enumerate
函数,该函数采用一个可迭代的(在这种情况下,为列名称的列表),并返回enumerate
为tuple
。例如:
(index, string)
然后,这些值将传递到每个(0, 'Australian Capital Territory')
(1, 'New South Wales')
...
(8, 'New Zealand')
调用中。
下面是用于创建数据集以复制您的数据集的代码(尽管,一个零DataFrame)以及用于创建跟踪的循环。
add_trace()
希望这会有所帮助!