{"id":14901,"library":"scatterd","title":"scatterd","description":"scatterd is a Python package designed for the easy and fast creation of beautiful scatter plots. It simplifies the process of data visualization, currently at version 1.4.2, with an active release cadence.","status":"active","version":"1.4.2","language":"en","source_language":"en","source_url":"https://github.com/erdogant/scatterd","tags":["plotting","scatter plot","visualization","data science"],"install":[{"cmd":"pip install scatterd","lang":"bash","label":"Install with pip"}],"dependencies":[],"imports":[{"note":"The primary plotting function/class is directly exposed as 'scatterd' within the 'scatterd' package.","wrong":"import scatterd","symbol":"scatterd","correct":"from scatterd import scatterd"}],"quickstart":{"code":"import pandas as pd\nimport numpy as np\nfrom scatterd import scatterd\nimport matplotlib.pyplot as plt\n\n# Sample data\nnp.random.seed(42)\ndata = {\n    'X': np.random.rand(100) * 10,\n    'Y': np.random.rand(100) * 10 + np.random.rand(100) * 2,\n    'Size': np.random.rand(100) * 50 + 10, # Example for variable point sizes\n    'Category': np.random.choice(['A', 'B', 'C'], 100)\n}\ndf = pd.DataFrame(data)\n\n# Create a basic scatter plot using the scatterd function\n# Assuming scatterd function accepts common plotting arguments like Matplotlib's scatter\nscatterd(x=df['X'], y=df['Y'], title='My First Scatter Plot',\n         xlabel='Feature X', ylabel='Feature Y', s=df['Size'], c=df['Category'],\n         colorbar_title='Category' # Example for categorical coloring\n        )\n\n# Display the plot. scatterd often leverages Matplotlib internally.\nplt.show()","lang":"python","description":"This example demonstrates how to create a simple scatter plot using `scatterd` with a Pandas DataFrame. It generates random data for X, Y, point size, and a categorical variable, then calls the `scatterd` function with appropriate arguments to visualize the data. It's assumed that `scatterd` internally uses or is compatible with Matplotlib for rendering, hence `matplotlib.pyplot.show()` is included to display the plot."},"warnings":[{"fix":"For very large datasets, use alternative visualization techniques like 2D histograms or density plots. For discrete data, consider jittering points or adjusting marker transparency (alpha).","message":"Be mindful of overplotting when dealing with large datasets or discrete variables. Multiple observations at the same coordinates may appear as a single point, misleading visual interpretation. Consider density plots or alpha blending for such cases.","severity":"gotcha","affected_versions":"All"},{"fix":"Always consider confounding factors and domain knowledge. Do not assume causal relationships solely based on visual correlation in scatter plots.","message":"Correlation shown in a scatter plot does not imply causation. A strong visual correlation between two variables does not mean one causes the other.","severity":"gotcha","affected_versions":"All"},{"fix":"Carefully examine outliers and their impact on the overall trend. Always check axis scales to ensure they are appropriate and not exaggerating or minimizing relationships.","message":"Ignoring outliers or misinterpreting the scale of axes can lead to incorrect conclusions about data trends and patterns. Discrepancies in scale or non-uniform scaling can distort the perceived relationships.","severity":"gotcha","affected_versions":"All"}],"env_vars":null,"last_verified":"2026-04-16T00:00:00.000Z","next_check":"2026-07-15T00:00:00.000Z","problems":[{"fix":"Run `pip install scatterd` to install the package.","cause":"The 'scatterd' package is not installed in the current Python environment.","error":"ModuleNotFoundError: No module named 'scatterd'"},{"fix":"Ensure that the data arrays passed to the `x` and `y` parameters are numeric (integers or floats). Convert data types using `df['column'].astype(float)` or similar methods if necessary.","cause":"Plotting functions expect numeric data for X and Y axes. If non-numeric data (e.g., strings) are passed, a TypeError will occur.","error":"TypeError: 'numpy.ndarray' object is not callable (or similar for non-numeric data)"}],"ecosystem":"pypi"}