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Cheetsheet

Cheetsheet

General

  • Getting help: help(my_function), help(my_module.my_function), help(my_variable.my_method)

  • Import a module: import my_module or import my_module as mm

  • Import a function from a module: from my_module import my_function

  • Creating a function:

def my_function(a, b = 3):
    my_output = a * b
    return my_output

  • Creating a for loop:

for i in my_list:
    do something with each i element of my_list
    each line does some operation
    there can be multiple lines
    all lines have to be INDENTED

for i in range(10):
    do something with i which takes values from 0 to 9

  • Creating an if statement:

if a > b:
    do something if a > b
elif a > c:
    if the first condition is unmet, do something if a > c
else:
    in all other cases do another operation
    each bloch can have multiple lines
    as in the for loop, the blocks have to be INDENTED

  • Having multiple blocks:

for i in my_list:
    print(i)
    if i > 5:
        new_var = i * 2

Numpy

  • Create zeros array: my_array = np.zeros((5,7))

  • Get value at row = 3, column = 4: my_value = my_array[3,4]

  • Get all columns of row = 3: my_array[3,:]

  • Create boolean array by a logical operation: my_boolean_array = my_array > 10

  • Check array size: my_array.shape

  • Get pixel values of image under mask: pixel_values = image[mask]

  • Flatten an array (make it 1D): array_1D = np.ravel(my_array)

Matplotlib

  • Plot an image:

plt.subplots(figsize=(10,10))
plt.imshow(my_image)
plt.show()

  • Histogram with specific bins:

plt.hist(my_data, bins = np.arange(0,1000,1))
plt.show()

Pandas

  • Create a Dataframe from list of dictionaries: my_dataframe = pd.DataFrame(my_dictlist)

  • Create a Dataframe from a 2D array with three columns:

my_dataframe = pd.DataFrame(my_2Darray, columns=['col1','col2','col3'])

  • Recover a the my_param column for all rows: my_dataframe.my_param or my_dataframe['my_param']

  • Calculate mean of a column called my_param: my_dataframe.my_param.mean()

  • Calculate statistic for full table: my_dataframe.mean()

Skimage

  • Import an image from your computer: skimage.io.imread('/path/to/your/file.tif')

  • Import an image from the web: skimage.io.imread('http://mysite/my_image.tif')

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