rileypeterson

from googletrans import Translator
import pandas as pd
translator = Translator()
df = pd.DataFrame({'Spanish':['piso','cama']})
df['English'] = df['Spanish'].apply(translator.translate, src='es', dest='en').apply(getattr, args=('text',))

rileypeterson

import logging
import time
import numpy as np

def prog_log(logger, percentage, pwidth=20, pchar="#"):
    """ Take a logger object and percentage and output a
    progress bar to the log
    """
    original_format = logger.handlers[0].formatter
    logger.info("Progress:")

rileypeterson

open -Fna /Applications/MySQLWorkbench.app/Contents/MacOS/MySQLWorkbench

from: https://stackoverflow.com/questions/21235894/how-to-open-multiple-model-database-in-mysql-workbench

rileypeterson

# UPDATE: He re-added the question here: https://stackoverflow.com/questions/52048919/how-to-incrementally-add-linear-regression-column-to-pandas-dataframe/52068085#52068085

# Some guy had this weird question on Stack Overflow about cummulatively applying linear regression to a dataframe
# He deleted the question (I don't think this operation is very useful), but I figured out a way to do it here:
# Pretty wacky
from io import StringIO
import pandas as pd
import numpy as np

df = pd.read_table(StringIO("""     a    b

rileypeterson

def A003417():
    n = 0
    while True:
        if n == 0:
            yield 2
        if n == 1:
            yield 1
        else:
            if (n+1) % 3 == 0:
                yield int(2 * ((n+1) / 3))

rileypeterson

# Your init script
#
# Atom will evaluate this file each time a new window is opened. It is run
# after packages are loaded/activated and after the previous editor state
# has been restored.
#
# An example hack to log to the console when each text editor is saved.
#
# atom.workspace.observeTextEditors (editor) ->
#   editor.onDidSave ->

rileypeterson

from functools import wraps
STRING1_LIST = ['A', 'B', 'C']
STRING2_LIST = ['D', 'E', 'F']
def type_checker(int1=None, string1=None, string2=None):
    """ Decorator function to check if int1 is an int and
        that string1 or string2 supplied is actually a valid string
    """
    if string1:
        s = 'string1'
        list_to_find_in = STRING1_LIST

rileypeterson

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
a = pd.DataFrame({'a':[0.25, 0.5, 0.15, 0], 'b':[0.15, 0.25, 0.35, 0.15], 
                  'c':[0.50, 0.15, 0.5, 0.35], 'd':[0.35, 0.35, 0.25, 0.5],})
fig, ax = plt.subplots()
x = a.index
indexes = np.argsort(a.values).T
heights = np.sort(a.values).T
order = -1

rileypeterson

ax1.set_zorder(ax2.get_zorder()+1) # put ax in front of ax2 
ax1.patch.set_visible(False) # hide the 'canvas' 

from: http://matplotlib.1069221.n5.nabble.com/Control-twinx-series-zorder-ax2-series-behind-ax1-series-or-place-ax2-on-left-ax1-on-right-td12994.html

rileypeterson

import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 50, 3001)
y = np.sin(3*x)
delta_x = x[1]
def second_order_central_fd(y, delta_x):
    """
    Return the second order central finite difference of a vector (i.e. d^2 y/ dx^2).
    Zero fills rollover. What it should probably do is a single order FDA
    or interpolate the endpoints.