peter.davidson pdavidsonFIA

## index.html
<!DOCTYPE html>
<meta charset="utf-8">
<style>

.links line {
  stroke: #999;
  stroke-opacity: 0.6;
}

.nodes circle {

## eiopa_scraper.py
import os
from datetime import date
import zipfile
import sqlite3
from sqlite3 import Error
import pandas as pd


def download_file(url: str,
                  workspace,  # url of the file to download

## gwp_anim.py
__author__ = """Peter Davidson FIA"""
__email__ = 'peter.davidson@wefox.com'
__version__ = '0.1'
__license__ = 'If you find this helpful, please say thank you'

import pandas as pd, numpy as np
def shear_array(df):
# This function just shears an array
# E.g. x = np.arange(9).reshape(3,3)
#      shear_array(x)

## eiopa_rfr.txt
{"eur": {"0": {"1": -0.00157, "2": -0.00129, "3": -0.00038, "4": 0.00096, "5": 0.00232, "6": 0.00381, "7": 0.00526, "8": 0.00667, "9": 0.00801, "10": 0.00921, "11": 0.01026, "12": 0.0112, "13": 0.01208, "14": 0.01284, "15": 0.01344, "16": 0.01388, "17": 0.01422, "18": 0.01454, "19": 0.01488, "20": 0.01527, "21": 0.01574, "22": 0.01627, "23": 0.01683, "24": 0.01741, "25": 0.018, "26": 0.01859, "27": 0.01918, "28": 0.01976, "29": 0.02033, "30": 0.02088, "31": 0.02141, "32": 0.02193, "33": 0.02243, "34": 0.02292, "35": 0.02338, "36": 0.02383, "37": 0.02426, "38": 0.02468, "39": 0.02508, "40": 0.02547, "41": 0.02584, "42": 0.02619, "43": 0.02654, "44": 0.02687, "45": 0.02719, "46": 0.02749, "47": 0.02779, "48": 0.02807, "49": 0.02834, "50": 0.02861, "51": 0.02886, "52": 0.02911, "53": 0.02934, "54": 0.02957, "55": 0.02979, "56": 0.03001, "57": 0.03021, "58": 0.03041, "59": 0.03061, "60": 0.03079, "61": 0.03097, "62": 0.03115, "63": 0.03132, "64": 0.03148, "65": 0.03164, "66": 0.0318, "67": 0.03195, "68": 0.0321,

## unpickle_to_excel.py
def unpickle_to_excel(filenames, params):
    import os
    import pandas as pd
    filename_pkl= os.path.splitext(filenames[0])[0] + '.pkl'
    filename_xl=os.path.splitext(filenames[0])[0] + '.xlsx'
    df = pd.read_pickle(filename_pkl)
    df.reset_index().to_excel(filename_xl, index=False)

if __name__ == '__main__':
    from context_menu import menus

## waterfall_chart_series.py
import matplotlib, matplotlib.pyplot as plt, matplotlib.ticker as tick
import seaborn as sns

def get_waterfall_colours(df, stocks=None):
    """Returns color palette for drawing waterfall bars"""
    default_colours = sns.color_palette("tab10")
    index_rgb = [3, 2, 0,5] # Red, green, blue, brown
    palette_subset = [default_colours[i] for i in index_rgb]
    colour_palette = []
    for index, value in df.items():
	<!DOCTYPE html>
	<meta charset="utf-8">
	<style>

	.links line {
	stroke: #999;
	stroke-opacity: 0.6;
	}

	.nodes circle {
	import os
	from datetime import date
	import zipfile
	import sqlite3
	from sqlite3 import Error
	import pandas as pd


	def download_file(url: str,
	workspace, # url of the file to download
	__author__ = """Peter Davidson FIA"""
	__email__ = 'peter.davidson@wefox.com'
	__version__ = '0.1'
	__license__ = 'If you find this helpful, please say thank you'

	import pandas as pd, numpy as np
	def shear_array(df):
	# This function just shears an array
	# E.g. x = np.arange(9).reshape(3,3)
	# shear_array(x)
	def unpickle_to_excel(filenames, params):
	import os
	import pandas as pd
	filename_pkl= os.path.splitext(filenames[0])[0] + '.pkl'
	filename_xl=os.path.splitext(filenames[0])[0] + '.xlsx'
	df = pd.read_pickle(filename_pkl)
	df.reset_index().to_excel(filename_xl, index=False)

	if __name__ == '__main__':
	from context_menu import menus
	import matplotlib, matplotlib.pyplot as plt, matplotlib.ticker as tick
	import seaborn as sns

	def get_waterfall_colours(df, stocks=None):
	"""Returns color palette for drawing waterfall bars"""
	default_colours = sns.color_palette("tab10")
	index_rgb = [3, 2, 0,5] # Red, green, blue, brown
	palette_subset = [default_colours[i] for i in index_rgb]
	colour_palette = []
	for index, value in df.items():