The arcpy.charts module allows you to visualize and explore your data to help uncover patterns, relationships, and structure that might not be apparent when looking at a table or map. These classes correspond to the charts available in ArcGIS Pro.

Class | Description |
---|---|

Bar charts summarize and compare categorical data using proportional bar lengths to represent values. | |

Box plots allow you to visualize and compare the distribution and central tendency of numeric values through their quartiles. | |

Calendar heat charts visualize patterns in temporal data by aggregating incidents into a calendar grid. | |

Data clocks visually summarize temporal data into two dimensions to reveal seasonal or cyclical patterns and trends over time. | |

Histograms visually summarize the distribution of a continuous numeric variable by measuring the frequency at which certain values appear in the dataset. | |

Line charts allow you to visualize change over a continuous range, such as time or distance. Visualizing change with a line chart allows for the overall trend to be displayed at once, and for multiple trends to be compared simultaneously. | |

Matrix heat charts analyze relationships between two categorical fields, which can be visualized by count or summarized by a numeric field. | |

Pie charts group data into slices to visualize part-to-whole relationships. | |

Quantile-quantile (QQ) plots are an exploratory tool used to assess the similarity between the distribution of one numeric variable and a normal distribution, or between the distributions of two numeric variables. | |

Scatter plots visualize the relationship between two numeric variables, where one variable is displayed on the x-axis, and the other variable is displayed on the y-axis. For each record, a point is plotted where the two variables intersect in the chart. When the resulting points form a nonrandom structure, a relationship exists between the two variables. | |

A scatter plot matrix is a grid (or matrix) of scatter plots used to visualize bivariate relationships between combinations of variables. Each scatter plot in the matrix visualizes the relationship between a pair of variables, allowing many relationships to be explored in one chart. |

##### Note:

The chart classes are subclasses of the Chart class and inherit all properties and methods from the parent class.