The chart explains the gender difference in school performance based on different states of india. Full project report
This a tutorial is to make a filled bar chart with color-fill mapped to data. The chart was created for this project.
Continue reading “Creating a filled barchart with matplotlib”
Often we want to know how a function is written in an imported package. This post explains how to examine the source code of a function/class.
To know where the package is installed:
For the package pandas:
To examine the source code of a given function or class, import the package inspect.
import inspect as insp
print insp.getsourcefile(pandas.DataFrame) # prints the path to source file
print insp.getsourcelines(pandas.DataFrame) # prints the source code
inspect package can be found here.
Viewing the source code from IPython Notebook
? to the function name inside the ipython-notebook cell to view code description and
?? for the entire source code.
pandas.DataFrame? # shows the docstring
pandas.DataFrame?? # shows the source code and docstring
top_n returns a
mask = [True, False, True, False, False ...] with “True” for top
n values. The mask is passed into an array as index to get “True” values.
import numpy as np
from scipy.stats import rankdata
def top_n(list_array, n = 1):
Returns a boolean mask with "True" for greatest "n" number of values
np_array = np.array(list_array)
# creating a mask
mask = np.zeros(len(np_array.flatten()), dtype=bool)
r =rankdata(np_array, method ="dense")
# rank matrix with highest value =1
for index, val in enumerate(r):
if val <= (n):
mask[index] = True
boolean_filter will return a list where boolean is true.
def boolean_filter(b_list, boolean):
This function returns values in b_list where the boolean is true
return [item for i, item in enumerate(b_list) if boolean[i]==True]
This is a wonderful article on how to serialize a python object into JSON