pandas 带散景的条形图熊猫数据框
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Bar chart pandas Dataframe with Bokeh
提问by akasolace
I have the following df:
我有以下 df：
[A B C D
1Q18 6.9 0.0 25.0 9.9
2Q17 NaN NaN NaN NaN
2Q18 7.1 0.0 25.0 4.1
3Q17 NaN NaN NaN NaN
3Q18 7.3 0.0 25.0 5.3
4Q17 NaN NaN NaN NaN
4Q18 7.0 0.0 25.0 8.3]
And I would like to obtain a graph such as 
我想获得一个图表，例如
I tried first with Bar(df) but it only graph the first column
我首先尝试使用 Bar(df) 但它只绘制第一列
p=Bar(df)
show(p)
I also tried:
我也试过：
p=Bar(popo, values=["A","B"])
show(p)
>raise ValueError("expected an element of either %s, got %r" % (nice_join(self.type_params), value))
ValueError: expected an element of either Column(Float) or Column(String), got array([[ 6.9, 0. ]])
thank you in advance for letting me what I am doing wrong
提前谢谢你让我做错了
cheers
干杯
回答by jezrael
In [Bokeh 0.12.6+] is possible use visual dodge:
在 [Bokeh 0.12.6+] 中可以使用视觉闪避：
from bokeh.core.properties import value
from bokeh.io import show, output_file
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure
from bokeh.transform import dodge
df.index = df.index.str.split('Q', expand=True)
df = df.sort_index(level=[1,0])
df.index = df.index.map('Q'.join)
#remove all NaNs, because not supported plotting
df = df.dropna()
print (df)
A B C D
1Q18 6.9 0.0 25.0 9.9
2Q18 7.1 0.0 25.0 4.1
3Q18 7.3 0.0 25.0 5.3
4Q18 7.0 0.0 25.0 8.3
output_file("dodged_bars.html")
df = df.reset_index().rename(columns={'index':'qrange'})
data = df.to_dict(orient='list')
idx = df['qrange'].tolist()
source = ColumnDataSource(data=data)
p = figure(x_range=idx, y_range=(0, df[['A','B','C','D']].values.max() + 5),
plot_height=250, title="Report",
toolbar_location=None, tools="")
p.vbar(x=dodge('qrange', -0.3, range=p.x_range), top='A', width=0.2, source=source,
color="#c9d9d3", legend=value("A"))
p.vbar(x=dodge('qrange', -0.1, range=p.x_range), top='B', width=0.2, source=source,
color="#718dbf", legend=value("B"))
p.vbar(x=dodge('qrange', 0.1, range=p.x_range), top='C', width=0.2, source=source,
color="#e84d60", legend=value("C"))
p.vbar(x=dodge('qrange', 0.3, range=p.x_range), top='D', width=0.2, source=source,
color="#ddb7b1", legend=value("D"))
p.x_range.range_padding = 0.2
p.xgrid.grid_line_color = None
p.legend.location = "top_left"
p.legend.orientation = "horizontal"
show(p)
回答by zipa
Your data is pivoted so I unpivoted it and then went with Barplot, hope this is what you need:
您的数据已旋转，因此我对其进行了旋转，然后进行了Bar绘图，希望这是您所需要的：
a = [6.9, np.nan, 7.1, np.nan, 7.3, np.nan, 7.0]
b = [0.0, np.nan, 0.0, np.nan, 0.0, np.nan, 0.0]
c = [25.0, np.nan, 25.0, np.nan, 25.0, np.nan, 25.0]
d = [9.9, np.nan, 4.1, np.nan, 5.3, np.nan, 8.3]
df = pd.DataFrame({'A': a, 'B': b, 'C': c, 'D': d}, index =['1Q18', '2Q17', '2Q18', '3Q17', '3Q18', '4Q17', '4Q18'])
df.reset_index(inplace=True)
df = pd.melt(df, id_vars='index').dropna().set_index('index')
p = Bar(df, values='value', group='variable')
show(p)
