David Yerrington dyerrington

## google_translate_api_demo.ipynb

      
              1 file
            
          
              0 forks
            
          
              1 comment
            
          
              0 stars
            
          
                dyerrington
                / google_translate_api_demo.ipynb
            
            
              Last active
              November 9, 2022 19:35
            
              
                Google Translate API demo tested with Python 3.9.x. I want to say this may not work so well with Python 3.10 for some reason but if you follow the guide I referenced otherwise, you should be in business. Highly recommended that you create a new Python environment before engaging with any serious development if you haven't done so.
              
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## config.md

      
              2 files
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                dyerrington
                / config.md
            
            
              Last active
              July 8, 2022 17:42
            
          
Installation

It's recommended that you install the requirements for these t5 models in a new environment since they are known to conflict with common Python package requirements in the scientific Python Stack.
Conda ENV Setup

Create

conda create -n nlp-t5

  
## finplot_example.py
import finplot as fplt
import yfinance

df = yfinance.download('AAPL')
d = df[['Open', 'Close', 'High', 'Low']].reset_index(drop=True)
fplt.candlestick_ochl(d)
fplt.show()

## ghcn_demo.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                dyerrington
                / ghcn_demo.ipynb
            
            
              Created
              February 9, 2021 03:36
            
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## m1_fix_5.1.2.event_loops_py.patch
--- eventloops.py-orig  2020-12-12 10:22:08.633178000 -0800
+++ eventloops.py       2020-12-12 10:22:56.335735100 -0800
@@ -20,7 +20,7 @@

     Checks if we are on OS X 10.9 or greater.
     """
-    return sys.platform == 'darwin' and V(platform.mac_ver()[0]) >= V('10.9')
+    return sys.platform == 'darwin' and V(platform.mac_ver()[0]) >= V('10.9') and platform.mac_ver()[2] != 'arm64'


## multi-roc_curve.py
## import any sklearn models and collect predictions / probabilities beforehand

import matplotlib.pyplot as plt
from cycler import cycler

## Line color config -- rather than create a structure with a finite color palette, use your own to cycle through a list.
default_cycler = (cycler(color=['r', 'g', 'b', 'y']) +
                  cycler(linestyle=['-', '--', ':', '-.']))

plt.rc('axes', prop_cycle = default_cycler)

## gist:6850e459c37b3f01e4049505c1634256
def fetch_states():
    """
    Return all <option> values for the <select> element with all states.
    """
    data = {}
    states = tree.xpath('//select[@name="state"]')
    try:
        for state in states[0].xpath('option'):
            data[state.attrib['value']] = state.text_content()
    except:

## test_station_data_availability.py
import requests, re

def test_station_data_availability(station_id):
    for year in range(1960, 2020 + 1):
        r = requests.get(f"https://www.ncei.noaa.gov/data/local-climatological-data/access/{year}/")
        matches = re.search(r"href=\"([0-9]{6}" +str(station_id) + ".csv)", r.text)
        if matches:
            print(station_id, " data exists for ", year)
        else:
            print(station_id, " data not found for ", year)

## alcohol_correlation.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                dyerrington
                / alcohol_correlation.ipynb
            
            
              Last active
              May 19, 2020 00:23
            
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## set_correlation_matrix_identity,py
import pandas as pd
import numpy as np
from sklearn.datasets import load_wine

# Load example wine dataset from sklearn
data = load_wine()

# Create a basic DataFrame
df = pd.DataFrame(data['data'], columns = data['feature_names'])
	import finplot as fplt
	import yfinance

	df = yfinance.download('AAPL')
	d = df[['Open', 'Close', 'High', 'Low']].reset_index(drop=True)
	fplt.candlestick_ochl(d)
	fplt.show()
	--- eventloops.py-orig 2020-12-12 10:22:08.633178000 -0800
	+++ eventloops.py 2020-12-12 10:22:56.335735100 -0800
	@@ -20,7 +20,7 @@

	Checks if we are on OS X 10.9 or greater.
	"""
	- return sys.platform == 'darwin' and V(platform.mac_ver()[0]) >= V('10.9')
	+ return sys.platform == 'darwin' and V(platform.mac_ver()[0]) >= V('10.9') and platform.mac_ver()[2] != 'arm64'
	## import any sklearn models and collect predictions / probabilities beforehand

	import matplotlib.pyplot as plt
	from cycler import cycler

	## Line color config -- rather than create a structure with a finite color palette, use your own to cycle through a list.
	default_cycler = (cycler(color=['r', 'g', 'b', 'y']) +
	cycler(linestyle=['-', '--', ':', '-.']))

	plt.rc('axes', prop_cycle = default_cycler)
	def fetch_states():
	"""
	Return all <option> values for the <select> element with all states.
	"""
	data = {}
	states = tree.xpath('//select[@name="state"]')
	try:
	for state in states[0].xpath('option'):
	data[state.attrib['value']] = state.text_content()
	except:
	import requests, re

	def test_station_data_availability(station_id):
	for year in range(1960, 2020 + 1):
	r = requests.get(f"https://www.ncei.noaa.gov/data/local-climatological-data/access/{year}/")
	matches = re.search(r"href=\"([0-9]{6}" +str(station_id) + ".csv)", r.text)
	if matches:
	print(station_id, " data exists for ", year)
	else:
	print(station_id, " data not found for ", year)
	import pandas as pd
	import numpy as np
	from sklearn.datasets import load_wine

	# Load example wine dataset from sklearn
	data = load_wine()

	# Create a basic DataFrame
	df = pd.DataFrame(data['data'], columns = data['feature_names'])