150 lines
8.3 KiB
Markdown
150 lines
8.3 KiB
Markdown
# User's Guide
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## Basic Concepts
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### How DataFrames is passed between nodes
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DataFrames are transmitted as JSON strings. When a DataFrame enters a node, it is reconstructed by deserializing the JSON string. Upon exiting, it is serialized back into a JSON string.
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Pandas's Index object is also processed the same way. For example, Pandas Columns and Pandas Index node return labels in a serialized Index format.
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### How to connect nodes for DataFrame JSON strings
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To connect the DataFrame JSON string output from one Pandas node to another, move the wire toward the top-left of the text field. You may need to hover around the corner to find the correct connection point.
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### How to add a node
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You can right-click, select **Add Node**, go to **Data Analysis**, and look for the following nodes:
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| Node Name | Functionality |
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| **Pandas Load CSV** | Load a CSV file |
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| **Pandas Load CSV With Encoding** | Load a CSV file not encoded in utf-8 |
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| **Pandas Load CSV With Index** | Load a CSV file containing index |
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| **Pandas Save CSV** | Save a DataFrame to a CSV file |
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| **Pandas Create** | Create a DataFrame from CSV text field |
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| **Pandas Create With Index** | Create a DataFrame from CSV text field containing index |
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| **Pandas Columns** | Extract column labels |
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| **Pandas Index** | Extract row labels (index) |
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| **Pandas Select Columns** | Select specific columns from a DataFrame |
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| **Pandas Select Rows** | Filter rows based on conditions |
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| **Pandas Iloc Row Series** | Select a row by row integer position |
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| **Pandas Loc Row Series** | Select a row by row label (index) |
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| **Pandas Loc Cell Str** | Select a cell by row label (index) and column label (index) |
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| **Pandas Join** | Join two DataFrames |
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| **Pandas Head** | Extract the first few rows |
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| **Pandas Show DataFrame** | Display DataFrame contents |
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| **Pandas Show Text** | Display Text |
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| **Pandas Summary** | Extract DataFrame statistics |
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| **Pandas Sort** | Sort DataFrame by a column |
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| **Pandas Series To String** | Convert Series to a displayable string |
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| **Pandas To String** | Convert DataFrame to a displayable string |
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| **MPL Bar Chart** | Generate a bar chart |
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| **MPL Line Plot** | Generate a line plot |
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| **MPL Scatter Plot** | Generate a scatter plot |
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A faster way is to double-click the canvas to open the node search dialog.
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The examples directory contains workflows that load data from an example dataset included in this package. These workflows should give you a good idea about how to use these nodes.
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## Loading data
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Use **Pandas Load CSV** node to load a CSV, or **Pandas Load CSV With Index** node if the CSV contains an index column. These nodes assume that the file is encoded in utf-8. If the file is not encoded in utf-8, use **Pandas Load CSV With Encoding** to specify the encoding of the file. This is necessary if the data was collected before utf-8 encoding became popular. For example, you can try "latin_1" for a file that contains accented characters in the US and Western Europe.
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These nodes emit the DataFrame in a JSON string.
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CSV file path is relative to the ComfyUI installation directory unless you specify the absolute file path.
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## Saving data
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Use **Pandas Save CSV** node to save the DataFrame to a CSV file.
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## Creating DataFrame on the UI
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Use **Pandas Create** or **Pandas Create with Index** nodes. These nodes display the multiline text area where you can enter the data in CSV format.
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If the data contains an index column, use **Pandas Create with Index** and specify the index column.
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## Extracting column and row labels
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Use **Pandas Columns** and **Pandas Index** nodes. As these nodes output JSON-serialized Index object, to display the value, use **Pandas Show Text** node as shown below:
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## Selecting columns and rows
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Use **Pandas Select Columns** for selecting columns.
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For rows, there are multiple options.
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Use **Pandas Select Rows** to select rows by a filter condition.
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You can use **Pandas Loc Row Series** to select a row by row label (index), or you can use **Pandas Iloc Row Series** to select a row by row integer position. Both nodes returns a JSON-serialized Series object.
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For **Pandas Loc Row Series**, data type of the labels needs to be specified as shown below:
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For **Pandas Iloc Row Series**, you only need to specify the row integer position:
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Note that in Pandas, integer position is an equivalent of an index in other software,
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while "index" means a unique label assigned to each row or column. See [pandas.DataFrame.iloc.html](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.iloc.html).
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## Selecting a cell by row label (index) and column label (index)
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Use **Pandas Loc Cell Str** for selecting a cell by row label (index) and column label (index). Data type of the labels needs to be specified as shown below:
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This node outputs the cell value as a string irrespective of the actual cell data type.
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## Joining DataFrames
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Use **Pandas Join**. You can select from inner, left, right, outer joins.
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First, use two **Pandas Load CSV** nodes to load two CSVs for the left DataFrame and right DataFrame.
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### Inner join
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Specify the common column in the "on column name" field, and set the join method to **inner** in the **Pandas Join** node.
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### Left join
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Specify the common column in the "on column name" field, and set the join method to **left** in the **Pandas Join** node.
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### Right join
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Specify the common column in the "on column name" field, and set the join method to **right** in the **Pandas Join** node.
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### Outer join
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Specify the common column in the "on column name" field, and set the join method to **outer** in the **Pandas Join** node.
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The workflow file examples/workflows/join.json contains all of the above cases.
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## Extract the first few rows
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Use **Pandas Head**.
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## Display text ##
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Use **Pandas Show Text** node.
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Currently this node is using the code taken from ComfyUI-Custom-Scripts's Show Text custom node (
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https://github.com/pythongosssss/ComfyUI-Custom-Scripts/blob/main/py/show_text.py).
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This node has been copied to display text without requiring the user to install the above custom nodes package. However, if you already have ComfyUI-Custom-Scripts, you can also use the Show Text node from the package.
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## Displaying DataFrame contents
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Use **Pandas Show DataFrame** node. When the number of rows is large, Pandas automatically hides middle rows during string conversion, so the display size should be always manageable.
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## Extracting DataFrame statistics
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Use **Pandas Summary** to extract statistics then connect the output to **Pandas Show Text** for display.
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## Sorting DataFrame by a column
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Use **Pandas Sort**.
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## Convert DataFrame to a string
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Use **Pandas To String**. This node is to convert the DataFrame to a displayable string, and this truncates the data when the data is large. This can be used to display the data content in a text display node (e.g. Show Text node). However, you can use Show DataFrame nodes to display the DataFrame content, so you do not normally need to use this.
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## Convert Series to a string
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Use **Pandas Series To String**. This node converts a Pandas Series to a displayable string. You can use this as an input to the **Pandas Show Text** node.
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## Displaying charts or plots
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Use one of the below:
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| Node | Purpose |
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| **MPL Bar Chart** | Generate a bar chart |
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| **MPL Line Plot** | Generate a line plot |
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| **MPL Scatter Plot** | Generate a scatter plot |
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