How forecast weekly sales?

I'm working on a forecasting weekly sales by category. I want to make sure I'm doing it correctly.

    date    DiningSales3/1/2015    2433343/8/2015    5566373/15/2015   554315......10/1/2017   343660

I've read Rob Hyndman website and see he recommends TBATS for weekly data. My date range is from 3/1/2015-10/1/2017. I want to predict the next 4 weeks. Here is my code:

dining.data <- read.csv("sales_dining.csv", fileEncoding="UTF-8-BOM")dining.df <- dining.data$DiningSalesdining.ts <- ts(dining.df,                  freq=365.25/7, start=2015+59/365.25)dining.tbats <- tbats(dining.ts)dining.fc <- forecast(dining.tbats, h=4)plot(dining.fc, ylab="dining orders")

The code runs but my predictions for the next 4 weeks seem way off. My questions are:

1. Did I use the correct frequency to get weekly data?
2. Is my start date correct? I want the start date to be 3/1/2015.
3. The next four predictions change the date to 10/7 to 2017.768. Is there a way to have the date in the results be in an actual date format?
4. Finally it seems like there isn't a lot out there for weekly forecast, rather monthly, annual or even daily or hourly. Is weekly data harder to have a more accurate prediction?