Download task_visualizations.py from lambdaofgod/github_search_visualizations: direct link, hf CLI and curl.
- Browser
- Download file 2.81 kB
-
https://huggingface.co/spaces/lambdaofgod/github_search_visualizations/resolve/42de6bd6bd22a42b6280ca9429753ae78d27b4b9/task_visualizations.py
- Command line
-
hf download hf://spaces/lambdaofgod/github_search_visualizations@42de6bd6bd22a42b6280ca9429753ae78d27b4b9/task_visualizations.py
-
curl -L -o task_visualizations.py https://huggingface.co/spaces/lambdaofgod/github_search_visualizations/resolve/42de6bd6bd22a42b6280ca9429753ae78d27b4b9/task_visualizations.py
2.81 kB
| import pandas as pd | |
| import ast | |
| import json | |
| import plotly.express as px | |
| import plotly.graph_objects as go | |
| class TaskVisualizations: | |
| def __init__( | |
| self, task_counts_path, selected_task_counts_path, tasks_with_areas_path | |
| ): | |
| self.tasks_with_areas_df = self.load_tasks_with_areas_df( | |
| task_counts_path, tasks_with_areas_path | |
| ) | |
| self.selected_tasks_with_areas_df = self.load_tasks_with_areas_df( | |
| selected_task_counts_path, tasks_with_areas_path | |
| ) | |
| def load_tasks_with_areas_df( | |
| cls, task_counts_path, tasks_with_areas_path="data/paperswithcode_tasks.csv" | |
| ): | |
| task_counts_df = pd.read_csv(task_counts_path) | |
| raw_tasks_with_areas_df = pd.read_csv(tasks_with_areas_path) | |
| return raw_tasks_with_areas_df.merge(task_counts_df, on="task") | |
| def get_topk_merge_others(cls, df, by_col, val_col, k=10, val_threshold=1000): | |
| sorted_df = df.copy().sort_values(val_col, ascending=False) | |
| topk_dict = ( | |
| sorted_df[[by_col, val_col]].set_index(by_col).iloc[:k].to_dict()[val_col] | |
| ) | |
| print(topk_dict) | |
| sorted_df[by_col] = sorted_df[by_col].apply( | |
| lambda k: k | |
| if k in topk_dict.keys() and topk_dict[k] >= val_threshold | |
| else "other" | |
| ) | |
| sorted_df = sorted_df.groupby(by_col).agg({val_col: sum}) | |
| return sorted_df | |
| def get_displayed_tasks_with_areas_df(cls, tasks_with_areas_df, min_task_count): | |
| displayed_tasks_with_areas_df = tasks_with_areas_df.dropna().copy() | |
| displayed_tasks_with_areas_df["task"] = displayed_tasks_with_areas_df.apply( | |
| lambda r: r["task"] if r["count"] >= min_task_count else "other", axis=1 | |
| ) | |
| displayed_tasks_with_areas_df = ( | |
| displayed_tasks_with_areas_df.groupby("area") | |
| .apply( | |
| lambda df: cls.get_topk_merge_others( | |
| df, "task", "count", val_threshold=min_task_count | |
| ) | |
| ) | |
| .reset_index() | |
| ) | |
| displayed_tasks_with_areas_df["task"] = ( | |
| displayed_tasks_with_areas_df["task"] | |
| + " " | |
| + displayed_tasks_with_areas_df["count"].apply(str) | |
| ) | |
| return displayed_tasks_with_areas_df | |
| def get_tasks_sunburst(self, min_task_count, which_df="selected"): | |
| if which_df == "selected": | |
| df = self.selected_tasks_with_areas_df | |
| else: | |
| df = self.tasks_with_areas_df | |
| displayed_tasks_with_areas_df = self.get_displayed_tasks_with_areas_df( | |
| df, min_task_count | |
| ) | |
| return px.sunburst( | |
| displayed_tasks_with_areas_df, path=["area", "task"], values="count" | |
| ) | |