Day #36 - Pandas Dataframe Learning's

	import numpy as np
	import pandas as pd
	#Tip #1
	#Data frame to matrix
	df = pd.DataFrame({'A':[1,2,3,4],'B':[5,6,7,8],'C':[5,6,7,8]})
	print(df)
	#Tip #2
	#Standardize value in columns
	df["A"] = (df["A"]-df["A"].mean())/np.std(df["A"])
	#Tip #3
	#Dynamically stardardize except last column
	for col in df.columns[:-1]:
	df[col] = (df[col] - df[col].mean())/ (np.std(df[col]))
	print(df)
	features = list(df.columns[:-1])
	#Tip #4 - Replance na values
	df = df.fillna(-9999)
	#Tip #5
	#Dynamically add columns
	for i in range(0,2):
	colname1 = str(5+i)
	col1 = i
	col2 = i+1
	print('colname', colname1)
	print('col1', col1)
	print('col2', col2)
	if(col2 < 2):
	df[colname1] = df[features[col1]]*df[features[col2]]
	print('newly added columns')
	print(df)

view raw pandasbasics.py hosted with ❤ by GitHub

Happy Learning!!!