<jupyter_start><jupyter_text>Visualize Tamai et al screen data<jupyter_code>import pandas

import plotly.graph_objects as go
import plotly.express as px
screen_df = pandas.read_table("data/tamai-screen/combined-results.tsv")
screen_df.notes.fillna("", inplace=True)
screen_df.head(2)
fig = px.scatter(
    data_frame=screen_df.reset_index(),
    x="compound_name",
    y="period_change",
    facet_row="concentration",
    facet_col="compound_set",
    hover_name="compound_name",
    hover_data=["notes", "period_before", "compound_set"],
    # same y-axis range as Figure 1A of Tamai et al.
    range_y=(-2, 5),
    labels={"period_change": "Period Change (hours)", "concentration": "Concentration"},
)
fig.update_xaxes(matches=None, showticklabels=False, title_text=None)
fig.show(renderer="notebook_connected")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1362559241706161, 'fraction_numerical': 0.004739336492890996, 'mean_word_length': 6.2844827586206895, 'pattern_counts': {'":': 2, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '473671', 'license': 'BSD-2-Clause-Patent', 'n_tokens_mistral': 311, 'n_tokens_neox': 301, 'n_words': 53, 'path': '20.plot-compounds.ipynb', 'repo_name': 'greenelab/circadian-clock-modulators', 'size': '844'}