I want to forecast some data, here is an example of the csv table:

I want to make predictions for every quarter until the end of Q4 2023.

I found an article which does something similar but doesn't have multiple value columns (Y axis)

I tried tailoring my code to allow for this but I get an error.

Here is my code(I've altered the contents to simplify my table, there were originally 12 columns not 5):

import pandas as pd
from datetime import date, timedelta
import datetime
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')
from statsmodels.tsa.seasonal import seasonal_decompose
from statsmodels.graphics.tsaplots import plot_pacf
from statsmodels.tsa.arima_model import ARIMA
import statsmodels.api as sm
import warnings
import plotly.graph_objects as go
# import make_subplots function from plotly.subplots
# to make grid of plots
from plotly.subplots import make_subplots

'set filepath'

inputfilepath = 'C:/Documents/' \
                    'Forecast/Input/' \
                        'Forecast Data csv.csv'
                        
df = pd.read_csv(inputfilepath)

print(df)

import plotly.express as px
figure = px.line(df, x="Time Period", 
                 y=("Fin","Legal","Leadership","Overall"),
                 title='Quarterly scores')

figure.show()

However, I am met with the following error:

ValueError: All arguments should have the same length. The length of argument y is 4, whereas the length of previously-processed arguments ['Time Period'] is 6

How would I alter my code to produce a graph that contains multiple y variables (Fin, Legal, Leadership, Overall)?

Additionally, this is the link to the article I found:

https://thecleverprogrammer.com/2022/09/05/business-forecasting-using-python/

CodePudding user response：

Looks like your "y" argument accepts only list [ele1, ele2], not a tuple(ele1, ele2). I changed the brackets to squares and I ran your code just fine:

    import plotly.express as px
    figure = px.line(df, x="Time Period", 
                     y=["Fin","Legal","Leadership","Overall"],
                     title='Quarterly scores')

figure.show()

produces: this