CODEWITHSUNDEEP
pythonpandasdataframe
mac
mac

Reputation: 3

Color 1 word in a text string in Pandas Dataframe and corresponding values

I am using jupyter notebook to return this dataframe. I am trying to color the word "Bullish" green and "Bearish" red. Also if it is bullish the Buy/Sell Trade price should be green and Bearish the Buy/Sell price should be Red. Thanks for your help!

Sample file here: https://drive.google.com/drive/folders/1WWdFlXIqQCM6LyeWZglPzqUwhCy3blTD?usp=sharing

Sample output

import pandas as pd
import numpy as np
from datetime import date
from datetime import timedelta 

df_rr = pd.read_csv("W:\mac\dev\py\RR.csv", parse_dates=["DATE"], index_col="DATE")
df_rr.loc["2021-03-10"]

EDIT 1

The code works but it drops my date column. DO you know what happened to it? Also when I use this code, I get the following error. I want to be able to return 1 date of data so that is why I use: df_rr.loc["2021-03-10"]

I get AttributeError: 'Styler' ojbect has no attribute 'loc'

is there a better way to limit by one date?

EDIT 2

3/12/2021 Thanks for your edit. One final thing, can you help make the text in the INDEX column for Bullish and Bearish colored as well. Really appreciate you.

FOLLOW UP - This works great but can I only have the words BULLISH and BEARISH colored instead of the full text string? Thanks!

EDIT 3

It looks the new code adds zeros to my values. How do you chop trailing zeros in the price columns? Thanks!

Screenshot

EDIT 4 - 4/2/2021

Here is the original data + code to load the data

Here is the view after I add in your code

3 questions:

  1. Why are there 0's being added to my data (in BUY TRADE & SELL TRADE Columns)?
  2. Is it possible to just have the Words BULLISH be GREEN, BEARISH BE RED and NEUTRAL be GRAY?
  3. DATE column gets changed to have time, can we remove the time?

Thanks as always!

Upvotes: 0

Views: 653

Answers (1)

Pygirl
Pygirl

Reputation: 13349

You can colour using style

def cts(x):
    c1 = 'color: red'
    c2 = 'color: green'
    c3 = 'color: black'
    if 'BULLISH' in x['INDEX']:
        return c3,c1,c1
    elif 'BEARISH' in x['INDEX']:
        return c3,c2,c2
    else:
        return c3,c3,c3

df = df.reset_index(drop=True).style.apply(cts,subset=['INDEX', 'BUY TRADE', 'SELL TRADE'], axis=1)

df:

enter image description here

EDIT:

df.loc['2020-12-07'].reset_index().style.apply(cts,subset=['INDEX', 'BUY TRADE', 'SELL TRADE'], axis=1)

enter image description here

EDIT2:

If you want to colour INDEX also do: (Initially I was showing black but for those you can change the color to red/green based on the condition)

if 'BULLISH' in x['INDEX']:
    return c1,c1,c1
elif 'BEARISH' in x['INDEX']:
    return c2,c2,c2
else:
    return c3,c3,c3

Upvotes: 1

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