Suppose we read some data into a pandas data frame:
data1 = pd.read_csv("data.csv", "\t")
The content looks like this:
And then define a function which should give us a horizontal bar chart, where the bar lengths represent values and the bars are labelled with the keys.
def barchart(data, labels):
pos = arange(len(data))+.5 # the bar centers on the y axis
barh(pos, data, align='center', height=0.25)
yticks(pos, labels)
Then we call the plot function like this:
barchart(data1["val"], data1["key"])
which gives us the following plot:
Now, what determines the order of the bars?
Suppose we want the bars in a special order, say [C, A, D, F, E, B]
, how can we enforce this?
If you directly read the key as the index with
In [12]: df = pd.read_csv('data.csv', '\t', index_col='key')
In [13]: df
Out[13]:
val
key
A 0.1
B 0.4
C 0.3
D 0.5
E 0.2
you can use ix
to get the index in a different order and plot it using df.plot
:
In [14]: df.ix[list('CADFEB')].plot(kind='barh')
Out[14]: <matplotlib.axes._subplots.AxesSubplot at 0x530fa90>
(Note that F is not given in the data, but you gave it as an example)
I modified original version of barchart. To specify order of bars I am using index set via ii column:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
def barchart(data, labels):
pos = np.arange(len(data)) + 0.5 # the bar centers on the y axis
plt.barh(pos, data.sort_index(), align='center', height=0.25)
plt.yticks(pos, labels.sort_index())
data1 = pd.DataFrame({'key': list('ABCDE'), 'val': np.random.randn(5)})
new_keys = list('EDACB')
data1['ii'] = [new_keys.index(x) for x in data1.key]
data1 = data1.set_index('ii')
barchart(data1["val"], data1["key"])
plt.show()
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