christinebuckler

\s(.*)

christinebuckler

# https://towardsdatascience.com/time-series-forecasting-based-on-the-trend-and-seasonal-components-26b92866e548

from statsmodels.tsa.seasonal import seasonal_decompose

def decompose(df):
    decomposition = sm.tsa.seasonal_decompose(df, model='additive', freq=365)
    trend = decomposition.trend
    seasonal = decomposition.seasonal
    residual = decomposition.resid
    fig = decomposition.plot()

christinebuckler

np.select(condlist, choicelist, default=0)

# EXAMPLE
CondList = [
   (data['FBG'] >= 126) | (data['HbA1c'] >= 6.5),
    ((data['FBG'] < 126) & (data['FBG'] >= 100)) | ((data['HbA1c'] < 6.5) & (data['HbA1c'] >= 5.7)),
    (data['FBG'] < 100) | (data['HbA1c'] < 5.7)]
ChoiceList = [2,1,0]
data.insert(1,'DM',np.select(CondList,ChoiceList,default=3))

christinebuckler

import math

def convert_size(size_bytes):
   if size_bytes == 0:
       return "0B"
   size_name = ("B", "KB", "MB", "GB", "TB", "PB", "EB", "ZB", "YB")
   i = int(math.floor(math.log(size_bytes, 1024)))
   p = math.pow(1024, i)
   s = round(size_bytes / p, 2)
   return "%s %s" % (s, size_name[i])

christinebuckler

-- In Teradata, you can use a Stored Procedure to loop over SQL statements with variable values. 
-- Here is an example of how you might do this:

REPLACE PROCEDURE Test (OUT r2 VARCHAR (3000)) 
BEGIN 
    DECLARE RowCnt INT; 
    DECLARE i INT; 
    DECLARE CurrRow INT; 
    DECLARE r VARCHAR (3000); 

christinebuckler

declare @SomeTempTable table
(
	Column1,
	Column2
)
declare @FiscalWeek int = 1
declare @FinalWeek int = ?
while @FiscalWeek <= @FinalWeek
begin
	insert into @SomeTempTable

christinebuckler

# use standard HTML comments
<!-- This is commented out. -->

christinebuckler

# Find
\((.*)

# Replace
($1) AS $1

# Example
,SUM(rtn_ttl_u
,SUM(rtn_ttl_u) AS rtn_ttl_u

christinebuckler

# standard imports
import os
import logging
import time
import yaml

# third party imports
import pandas as pd
import dask.dataframe as dd
from dask.distributed import Client, LocalCluster

christinebuckler

import os
import multiprocessing

# get the number of logical cpu cores
n_cores = os.cpu_count()
n_cores = multiprocessing.cpu_count()

# get total physical memory
# https://stackoverflow.com/questions/22102999/get-total-physical-memory-in-python
# For MacOS, as per user reports, this works with Python 3.7 but not with Python 3.8