# Context:
USER: how can i set the bar color/fill style for each edit-format
ASSISTANT: To set the bar color/fill style for each edit-format, you need to modify the `show_stats` function in the `benchmark/benchmark.py` file.
Here are the steps:
1. Define a dictionary mapping each edit-format to a specific color or fill style.
2. Use the `color` or `fill` parameter in the `plot` function to set the color or fill style for each bar.
Here is the code change:
```python
benchmark/benchmark.py
<<<<<<< ORIGINAL
fig, ax = plt.subplots(figsize=(10, 6))
df_grouped2.unstack().plot(kind="barh", ax=ax)
=======
fig, ax = plt.subplots(figsize=(10, 6))
color_map = {"edit_format1": "blue", "edit_format2": "green", "edit_format3": "red"} # Define your color map here
df_grouped2.unstack().plot(kind="barh", ax=ax, color=[color_map[i] for i in df_grouped2.index])
>>>>>>> UPDATED
```
Please replace `"edit_format1"`, `"edit_format2"`, and `"edit_format3"` with your actual edit formats, and `"blue"`, `"green"`, and `"red"` with your desired colors.
# Context:
USER: sort the grouped columns by descending average
ASSISTANT: To sort the grouped columns by descending average, we need to modify the `show_stats` function in the `benchmark/benchmark.py` file. Specifically, we need to sort the `df_grouped` DataFrame by its values in descending order.
Here is the change:
```python
benchmark/benchmark.py
<<<<<<< ORIGINAL
df_grouped = df.groupby(["model", "edit_format"])["pass_rate_1"].mean()
=======
df_grouped = df.groupby(["model", "edit_format"])["pass_rate_1"].mean().sort_values(ascending=False)
>>>>>>> UPDATED
```
This change will sort the grouped DataFrame `df_grouped` by its values in descending order. The `ascending=False` argument in the `sort_values` function ensures that the sorting is done in descending order.