Gantt Chart source data preparation

I have this code.

import yfinance as yfimport numpy as npimport pandas as pddf = yf.download('TSLA', start = '1991-01-01')data = df.Close.loc[(df.index>='1991-01-01')]data=data.to_frame()sma_s = 50sma_l = 100data['sma_s'] = data.Close.rolling(sma_s).mean()data['sma_l'] = data.Close.rolling(sma_l).mean()data['day'] = data.index.daydata.dropna(inplace=True)data['position_1_-1'] = np.where(data['sma_s']>data['sma_l'], 1, -1)data['position_1_0'] = np.where(data['sma_s']>data['sma_l'], 1, 0)data['position_0_-1'] = np.where(data['sma_s']>data['sma_l'], 0, -1)data               Close       sma_s       sma_l    day position_1_-1   position_1_0    position_0_-1Date                            2010-11-17  1.966000    1.476147    1.399193     17             1              1                02010-11-18  1.992667    1.488387    1.403193     18             1              1                02010-11-19  2.066000    1.502813    1.407967     19             1              1                02010-11-22  2.226667    1.519720    1.415593     22             1              1                02010-11-23  2.304667    1.537653    1.425840     23             1              1                0

This is a Simple Moving Average strategy and the columns beginning with position indicates our Long/Short position such that position_1_-1 is both Long and Short. position_1_0 is Long Biased. And position_0_-1 is short biased. I want to use the day column to determine start and end of a trend within the month. And plot Gantt Charts.

import altair as altimport pandas as pdsource = pd.DataFrame([    {"task": "A", "start": 1, "end": 3},    {"task": "B", "start": 3, "end": 8},    {"task": "C", "start": 8, "end": 10}])alt.Chart(source).mark_bar().encode(    x='start',    x2='end',    y='task')

The start and end has to be monthwise. What is the best way to do this?