How do I analyze custom data (lets say a csv file based on  earning reports or some other events) using python (pandas/numpy) and generate buy/sell signals and backtest ?

A. Can I analyse the data in quantconnect so I don't have to uplaoda csv file and it could work in real time

B. If I analyse the data outside (lets say google colab), generate a CSV file with buy and sell indicator. Now can I upload to quantconnect and backtest it?

This is not the strategy I am considering but just to give an idea lets say I have earning report from some source which I downlaoded (or used api) and processed with python/pandas (on google colab or quantconnect) and created  a csv like this. 

Date      Symbol     EPS.   Rating.    Buy_indicator.  Sell_indicator.  Position 

2020-1-1 APPL         23    Good.      1                      0                   1

2020-1-2 GOOG        12     Good      1                      0                   1

2020-04-1 APPL      30     Good      1                      0                  2

2020-04-2 GOOG     11      Bad        0                     1                   1

2020-07-1 APPL      25     Neutral   0                    0                  2

2020-07-2 GOOG    10      Bad         0                    0                  0

Now I want to the load the above csv data (if not created within quantconnect) in Quantconnect and backtest the strategy using buy/sell/positon indicators.