nickwan

def get_xz_at_y(row, y_target=0.0):
    """
    Given a row of Baseball Savant pitch data and a target y (distance from plate),
    return the (x, z) location of the pitch at that y.
    
    Converted this via Gemini and the Alan Nathan spreadsheet 
    https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fbaseball.physics.illinois.edu%2FTrajectoryCalculator-new-3D-May2021.xlsx&wdOrigin=BROWSELINK
    If you're using pandas and numpy, you should be good to go. Sorry, I'm not good at dependencies and docs GIGGLECHAD     
        
    Parameters

nickwan

# data load (with lau's var names) 
week1_df = pd.read_csv(weeks_fns[0])
data_dir = '/content/drive/My Drive/nflfastR-data'
data_files = [f'{data_dir}/data/{x}' for x in os.listdir(f"""{data_dir}/data""") if (x.endswith('.parquet')) & ('2018' in x)]
fastr_18 = pd.DataFrame()
for fn in tqdm(reversed(data_files)):
  _df = pd.read_parquet(fn)
  fastr_18 = fastr_18.append(_df,ignore_index=True)

roster_data = pd.read_csv(f"{data_dir}/roster-data/roster.csv")

nickwan

Keybase proof

I hereby claim:

• I am nickwan on github.
• I am nickileaks (https://keybase.io/nickileaks) on keybase.
• I have a public key ASBwZD316-MGh5eQ1GmdxIQt1x7copvrzeeuvONWRPteUAo

To claim this, I am signing this object:

nickwan

### Mostly taken from this blog post
# http://superfluoussextant.com/circlepusher.html

import random
from PIL import Image, ImageDraw
import math

class Circle:
    def __init__(self, radius, location, color):
        """

nickwan

def generate_tweets(model, corpus, char_to_idx, idx_to_char, n_tweets=10): 
#     model.load_weights('weights.hdf5')
    tweets = []
    spaces_in_corpus = np.array([idx for idx in range(CORPUS_LENGTH) if text[idx] == ' '])
    for i in range(1, n_tweets + 1):
        begin = np.random.choice(spaces_in_corpus)
        tweet = u''
        sequence = text[begin:begin + MAX_SEQ_LENGTH]
        tweet += sequence
        for _ in range(100):

nickwan

import os
import glob
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

def convert_date(ser):
    return ser[:10]