Merging of values in the columns of a dataframe

Question

I have a dataframe

import yfinance as yf
import numpy as np
from scipy.signal import argrelextrema
import matplotlib.pyplot as plt
import pandas as pd

company_name = "INFY.NS"
df = yf.Ticker(company_name).history(period='400d', interval='1D')

Now, I have a dataframe as df1. I am doing calculations for get max and min values.

n = 2
df['min'] = df.iloc[argrelextrema(df['Close'].values, np.less_equal,order=n)[0]]['Close']
df['max'] = df.iloc[argrelextrema(df['Close'].values, np.greater_equal,order=n)[0]]['Close']
print()

Thus dataframe looks like this

But, instead of these 2 columns i.e. max and min, I want only one column named MACD and wanted to add values of max and min columns in it. Thus,

if max is none and min has value, add in MACD column and vice versa
if max and min are both Nan, drop the row.

What is the best way to do this?

It's recommended to add your data as text, we can not copy the contents from image. — ThePyGuy
– ThePyGuy, Commented May 22, 2021 at 6:12
Rather than adding a data frame, only by running the lines of code, all data is available @ThePyGuy. That's why gave the code, kindly check — sam
– sam, Commented May 22, 2021 at 6:21
And that requires one to install yfinance. Anyways, it's about preferences, that was just a gentle suggestion. — ThePyGuy
– ThePyGuy, Commented May 22, 2021 at 6:25

sam · Accepted Answer · 2021-05-22 06:29:26Z

1

I have got the answer to merge the columns and removing Nan columns, posting the code here.

df['total'] = df['min'].combine_first(df['max'])
df = df.dropna(subset=['total'])

answered May 22, 2021 at 6:29

sam

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