How to predict next visit date based on this data I have a dataset shown below. Here, status is if visit has been done or not and schedule is if next_action_scheduled.

df = 

visit_date |status |scheduled_visit

2018-09-13|1|0000-00-00

2018-11-13|1|0000-00-00

2019-01-13|1|0000-00-00

2019-03-13|0|0000-00-00

2019-05-13|0|0000-00-00


So consider this case like user is visiting in every 2 month.

I would like to find this pattern for all users based on the historical visits with the customer. I would like to find the next predicted visit for that customer and if we missed that visit, then I ask "Do you want to schedule a visit" Or "You missed a visit with this customer."

I'm new in Ml. I tried to use RNN for time series forecasting but I'm getting a really high error rate. Prediciton is nowhere close. What model/algorithm I should use and learn about to make a model for this? I want to create a solution like if I feed in the user_id it will check all these values and send notification within app. 

Thank you
If you plot days since the first visit vs the visit number, this ends up being a simple regression problem.

import pandas as pd

data = pd.read_csv('data.txt', '|')
data['visit_date'] = pd.to_datetime(data['visit_date'])
data['days_since_first_visit'] = (data['visit_date'] - data['visit_date'][0]).map(lambda delta: delta.days)
data = data.reset_index()

data.plot('index', 'days_since_first_visit')




I would recommend using a library like scikit-learn or statsmodels to do the regression.