| core_list_sources | List all available data sources.
Returns a list of unique source_ids to be used for other queries.
Source type is included in the source_id string.
While drafting SQL queries use appropriate syntax as per source type. |
| core_list_tables | Lists names of all tables/datasets in a given data source.
Use run_query with appropriate SQL query to determine table structure
Args:
source_id: The data source to list tables from |
| core_run_query | Run query against specified source
For both csv and parquet sources, use DuckDB SQL syntax
Use 'CSV' as the table name for csv sources.
Use 'PARQUET' as the table name for parquet sources.
This will return a query_id, which can be referenced while calling other Zaturn tools.
Args:
source_id: The data source to run the query on
query: SQL query to run on the data source |
| core_show_query_result | Show stored result for query_id in markdown table format |
| visualizations_scatter_plot | Make a scatter plot with the dataframe obtained from running SQL Query against source
If this returns an image, display it. If it returns a file path, mention it.
Args:
query_id: Previously run query to use for plotting
x: Column name from SQL result to use for x-axis
y: Column name from SQL result to use for y-axis
hue: Optional String; Column name from SQL result to use for coloring the points |
| visualizations_line_plot | Make a line plot with the dataframe obtained from running SQL Query against source
Args:
query_id: Previously run query to use for plotting
x: Column name from SQL result to use for x-axis
y: Column name from SQL result to use for y-axis
hue: Optional; column name from SQL result to use for drawing multiple colored lines |
| visualizations_histogram | Make a histogram with a column of the dataframe obtained from running SQL Query against source
Args:
query_id: Previously run query to use for plotting
column: Column name from SQL result to use for the histogram
hue: Optional; column name from SQL result to use for drawing multiple colored histograms
bins: Optional; number of bins |
| visualizations_strip_plot | Make a strip plot with the dataframe obtained from running SQL Query against source
Args:
query_id: Previously run query to use for plotting
x: Column name from SQL result to use for x axis
y: Optional; column name from SQL result to use for y axis
hue: Optional; column name from SQL result to use for coloring the points
legend: Whether to draw a legend for the hue |
| visualizations_box_plot | Make a box plot with the dataframe obtained from running SQL Query against source
Args:
query_id: Previously run query to use for plotting
x: Column name from SQL result to use for x axis
y: Optional; column name from SQL result to use for y axis
hue: Optional column name from SQL result to use for coloring the points |
| visualizations_bar_plot | Make a bar plot with the dataframe obtained from running SQL Query against source
Args:
query_id: Previously run query to use for plotting
x: Column name from SQL result to use for x axis
y: Optional; column name from SQL result to use for y axis
hue: Optional column name from SQL result to use for coloring the bars
orient: Orientation of the box plot, use 'v' for vertical and 'h' for horizontal |