[[user]] Show map of suppliers going to countries

To show a map of suppliers going to countries, we will first load the provided CSV file, trade-register.csv, taking into account the specified lines to skip and file encoding. After loading the data, we will analyze it to understand the relationships between suppliers and recipient countries. This will help us in plotting the map that visualizes these relationships.

With the data successfully loaded, we can see that it contains information about arms trades between countries, including the recipient and supplier countries, the year of order, weapon designation and description, and other relevant details.

To visualize the suppliers going to different countries on a map, we will aggregate the data to identify unique pairs of supplier and recipient countries. Then, we will plot these relationships on a world map. This visualization will help us understand the global distribution of arms supplies.

It seems there was an issue retrieving the geographical coordinates for the sample country using Geopy. This could be due to various reasons such as network issues, incorrect country names, or limitations of the geocoding service. To ensure we can plot the suppliers going to countries accurately, let's try a different approach.

We will use a predefined list of country names and their corresponding coordinates. This will allow us to bypass the need for real-time geocoding and directly map the supplier-recipient relationships on a world map.

Let's proceed with this alternative approach.

Now that we have a working method to retrieve geographical coordinates for countries using a predefined list, we'll proceed to map the relationships between suppliers and recipient countries. This will involve plotting lines from the geographical location of the supplier to the recipient country on a world map.

Let's start by obtaining coordinates for all unique supplier and recipient countries in our dataset, then plot these relationships.

Given the limited set of predefined country coordinates, we have a subset of valid country coordinates that match our predefined list. This means we can only plot relationships for these countries.

Next, we will plot lines on a world map representing the flow of arms supplies from suppliers to recipient countries, focusing on the subset of countries for which we have valid coordinates.

We have successfully plotted the relationships between suppliers and recipient countries on a world map for the subset of countries for which we had valid coordinates. This visualization represents the flow of arms supplies from suppliers to recipient countries, highlighting the global distribution of these supplies.

If you have any further questions or need additional analysis, please feel free to ask!

[[user]] How can we get the latitude + longitude for the whole map?

To get the latitude and longitude for all countries involved in the trade register, we'll first extract the unique list of countries from both the Supplier and Recipient columns. Then, we'll use the geopy library to fetch the latitude and longitude for each country.

Let's start by extracting the unique list of countries.

Now that we have the unique list of countries, we will proceed to fetch the latitude and longitude for each country using the geopy library. This process may take some time due to the number of countries and potential rate limits of the geocoding service.

We'll start by fetching coordinates for a subset of countries to demonstrate the process.

To fetch the latitude and longitude for all countries involved in the trade register, we'll first load the provided dataset. Then, we'll extract the unique list of countries from both the Supplier and Recipient columns and use the get_coordinates function to fetch the geographical coordinates for each country.

Let's start by loading the dataset and extracting the unique countries.

Now that we have the get_coordinates function ready, let's proceed to fetch the latitude and longitude for each unique country involved in the trade register. This process may take some time due to the number of countries and potential rate limits of the geocoding service.

We'll start by fetching coordinates for a subset of countries to ensure the process works as expected.

The process successfully fetched latitude and longitude coordinates for a subset of countries from the unique list. However, some countries, like Russia in this case, returned None values. This could be due to various reasons such as limitations in the geocoding service or mismatches between country names in the dataset and those recognized by pycountry.

Given this success with a subset, we can proceed to fetch coordinates for all unique countries involved in the trade register. Please note that due to potential rate limits of the geocoding service, this process may take some time.

[[user]] Can you now visualize the graph?

To visualize the geographical distribution of countries involved in the trade register, we'll create a map. This map will display markers for each country, indicating their location based on the latitude and longitude we've obtained.

Let's proceed to create the map visualization.

The geographical distribution of countries involved in the trade register has been visualized on a global map. Each marker represents a country, plotted based on the latitude and longitude coordinates we obtained. This visualization provides a clear view of the global spread of countries involved in the trade register.

If you have any more questions or need further analysis, feel free to ask!

[[user]] I would like to make a map that connects the supplier countries with the reciever countries

To create a map that connects supplier countries with recipient countries, we'll first load the provided dataset. Then, we'll extract the unique pairs of supplier and recipient countries and use the previously obtained geographical coordinates to plot lines connecting these pairs on a map.

Let's start by loading the dataset and extracting the necessary information.

Now that we have loaded the dataset, let's proceed to extract the unique pairs of supplier and recipient countries. We will then use these pairs along with the previously obtained geographical coordinates to plot lines connecting supplier countries to recipient countries on a map.

Now that we have the unique pairs of supplier and recipient countries, we will proceed to create a map visualization. This map will include lines connecting each pair of supplier and recipient countries, representing the trade relationships between them.

To achieve this, we'll use the geographical coordinates obtained earlier for each country. If a country's coordinates are not available, that particular connection will be skipped in the visualization.

Let's start by preparing the data needed for plotting these connections.

[[user]] Can you visualize the top 100 supplier to receiver relationships, can you color each line differently and have the thickness of the line represent the amount of transfers between each?

To visualize the top 100 supplier to receiver relationships, with each line colored differently and the thickness representing the amount of transfers, we'll first need to aggregate the data to determine the top relationships based on the total number of transfers. Then, we'll use the geographical coordinates to plot these relationships on a map.

Let's start by aggregating the data to find the top 100 relationships.

With the top 100 supplier to receiver relationships identified based on the total number of transfers, we can now proceed to visualize these relationships on a map. Each line will be colored differently, and the thickness of each line will represent the amount of transfers between each pair.

Let's prepare the data for plotting, including obtaining geographical coordinates for each country involved in these top relationships.

With the data prepared, showing a sample of the top 100 supplier to recipient relationships along with their coordinates and transfer amounts, we can now proceed to visualize these relationships on a map. Each line will be uniquely colored, and the thickness of each line will represent the amount of transfers between each pair.

Let's create the visualization.

[[user]] Can you make the entire line highlight when I hover over it?

To make the entire line highlight when hovered over, we'll modify the visualization to include hover interactions that highlight the entire line. This will involve adjusting the line properties in the Plotly visualization to ensure that the hover effect is applied correctly.

Let's update the visualization accordingly.

[[user]] Can you now show me the top 200 relationship?

To visualize the top 200 supplier to receiver relationships, we'll first need to aggregate the data again to determine these relationships based on the total number of transfers. After that, we'll use the geographical coordinates to plot these relationships on a map, similar to the previous visualization but with more relationships included.

Let's start by aggregating the data to find the top 200 relationships.

With the top 200 supplier to receiver relationships identified based on the total number of transfers, we can now proceed to visualize these relationships on a map. Each line will be colored differently, and the thickness of each line will represent the amount of transfers between each pair.

Let's prepare the data for plotting, including obtaining geographical coordinates for each country involved in these top relationships.

With the data for the top 200 supplier to recipient relationships prepared, including their coordinates and transfer amounts, we can now proceed to visualize these relationships on a map. Each line will be uniquely colored, and the thickness of each line will represent the amount of transfers between each pair.

Let's create the visualization for the top 200 relationships.

[[user]] Can you give me a chart of sales that originate from the US to the recipient countries? Can you also make the earth be color of #1c4a44 and the water be #1a1d1e?

To create a chart of sales originating from the United States to various recipient countries, we will first filter the data to include only those transactions where the supplier is the United States. Then, we will visualize these relationships on a map, with the earth colored #1c4a44 and the water #1a1d1e.

Let's start by filtering the data for transactions originating from the United States.

Now that we have the data for sales originating from the United States to various recipient countries, we can proceed to visualize these relationships on a map. We will color the earth #1c4a44 and the water #1a1d1e as requested.

Let's create the visualization.

The chart visualizing sales from the United States to various recipient countries has been successfully created and displayed. The visualization includes markers for each recipient country, with the size of each marker representing the volume of transfers. Additionally, the earth is colored #1c4a44 and the water #1a1d1e, as requested.

If you have any more questions or need further analysis, feel free to ask!

[[user]] So the chart is not quite what I am looking for, I would like to connect the supplier countries to the recipient countries and have the thickness of the line represent the amount of transfers between each? I would also like the connection between each country be a different color

To create a visualization that connects supplier countries to recipient countries with lines whose thickness represents the amount of transfers, and each connection having a different color, we'll first need to filter the data for transactions where the supplier is the United States. Then, we'll prepare the data by obtaining geographical coordinates for each country involved and plot these relationships on a map.

Let's start by filtering the data for transactions originating from the United States and preparing it for visualization.

With the data for sales originating from the United States to various recipient countries prepared, including their coordinates and transfer amounts, we can now proceed to visualize these relationships on a map. Each line will be uniquely colored, and the thickness of each line will represent the amount of transfers between each pair.

Let's create the visualization for connections originating from the United States.

[[user]] Add a point to the end of the line, also make the lakes be the same color as the ocean and show the country borders

To enhance the visualization by adding a point to the end of each line, making lakes the same color as the ocean, and showing country borders, we'll modify the existing map accordingly. Let's proceed with these adjustments.

[[user]] Also change the color of the paper from white to be #111

[[user]] Remove the outlines between countries actually, and only show the dot on a country that has more than 10 transfers

To adjust the visualization according to your request, we'll remove the outlines between countries and only display a dot on countries that have more than 10 transfers. Let's proceed with these modifications.

[[user]] Hmm, just remove the dots entirely I guess, can you also change the colors to be within a smaller band of reds and blues?

To adjust the visualization by removing the dots entirely and changing the colors to be within a smaller band of reds and blues, we'll update the map accordingly. Let's proceed with these changes.

The visualization has been updated to remove the dots entirely and to alternate the colors of the connections between a smaller band of reds and blues. Each line represents a connection from the United States to a recipient country, with the thickness indicating the volume of transfers. The map's background and water bodies have been adjusted according to your specifications.

If there's anything more you'd like to explore or adjust, feel free to let me know!