README.rst

Python basics

List

my_list = []
my_list = [1,2,3,4,'blabla']

Add an element to a list:

a.append(1)

Access an element at index i

a[i]

Dictionary

my_dict = {}
my_dict = {key1:val2, key2:val2, ...}

my_dict['key'] = val

for key in my_dict.keys():
    print (key, my_dict[key])

Read and write file using 'with'

Avoid closing the file using with:

# Open file in read mode:
# the file closes automatically at the end of the with block
with open('filename.csv', 'r') as f_in:
    for line in f:
        if "someword" in line:
            # do something
            pass
        print line.split(',')

# Open the file in write mode, and create it if it doesn't exist:
# create a csv file type output:
with open('filename.csv', 'w+') as f_out:
    f_out.write('something,something_else,last_thing\n')

# Open the file in append mode:
# Will continue writing at the end
with open('filename.csv', 'a') as f_out:
    f_out.write('some_more,more_else,more_last_thing\n')

Use Pandas' read_csv to read csv file to data frame

from pandas import read_csv
df = read_csv('filename.csv')

print (df['something'])

# For numerical columns, min, max, mean, ...
df['timing'].min()
df['ratio'].unique()

# Apply constraints to print only rows of interest:
df.loc[(df['ratio'] == 5) & (df['flux'] == 2000)]

ipython (console)

Auto reload externally loaded files:

%load_ext autoreload
%autoreload 2

Paste code copied onto memory from somewhere else:

%paste
%cpaste

jupyter notebook

Show figures inline:

%matplotlib inline
%config InlineBackend.figure_format='retina'