The above command helps us visualize the data set. We can use the command df.plot(kind='line') and you will get the following chart, yes it really is that simple.

The program has requested data from the data server written it into Pandas Data Frame format and output the data in a table format.Īs you can see we have got data for the period we specified in a data frame which is similar to a table but the cool thing about Pandas is its ability to manipulate data and store data in various forms.īefore we dig deeper let’s just look a some basic commandĭf.head() - This will give us the first 5 lines of dataĭf.tail() - This will give us the last 5 lines of data Once you can copy the code and substituted your api_key you can run the program and you should get the following. Don't forget to substitute your api_key.Ĭopy the following code, The first line of cope makes and request to the data server and formats the returned JSON data as a Pandas Data Frame, the second line of code set the index for the data to the date field so it is displayed in date order, the third line of code 'df' outputs the data frame in a nice format.ĭf = pd.read_json(''+currency+'&api_key='+api_key+'&start_date='+start_date+'&end_date='+end_date+'&format='+format+'&fields='+fields) In the next cell type or copy the following variables, here we are setting up into settings we are going to pass in the data request. This command imports the Pandas Data Frame for use in our notebook you can read more about Pandas here In the cell write the following command and click run: Now that we have the API Key we can get startedĬlick on the scissor sign (third from the left under Edit) three times this just clears out the welcome content so we can start coding.

Once you have registered an account you will find your API Key under the myAccount page. Once you have started the notebook let's get an API key from account is free for up to 1000 requests a month. Wait a few seconds at this will launch a Jupyter Notebook for you in your browser Open your favorite browser and navigate to Select the 'Classic Notebook' link as shown below. Today we will look at how to get, change and store forex data from a JSON API and in the process learn about Pandas, DataFrame and Jupyter Notebook. Jupyter Notebook is an open-source web application that allows you to create documents and program various languages. Pandas is an open-source Python library that lets you manipulate data quickly including storing it in various forms. Before we start here is an overview of the libraries and setup we will be using in the tutorial. The tutorial assumes little or no knowledge of python. This is a beginner's tutorial for those who are new to pandas or data visualization.

Tradingview python jupyter notebook