import pandas as pd import matplotlib.pyplot as plt # Data for New York hourly forecast data = { "Time": ["3 PM", "6 PM", "9 PM", "12 AM", "3 AM", "6 AM", "9 AM", "12 PM", "3 PM"], "Temp (°C)": [26, 24, 23, 22, 21, 20, 23, 28, 28], "Temp (°F)": [79, 75, 73, 72, 70, 68, 73, 82, 82], "Condition": [ "Mostly sunny", "Clear", "Clear", "Clear", "Clear", "Sunny", "Mostly sunny", "Sunny and warm", "Continued warmth" ] } df = pd.DataFrame(data) # Display styled table with color def color_temp(val): if isinstance(val, (int, float)): if val >= 28: return 'background-color: #ff9999' # hot elif val >= 24: return 'background-color: #ffd699' # warm elif val >= 20: return 'background-color: #ffffb3' # mild else: return 'background-color: #c2f0c2' # cool return '' styled_df = df.style.applymap(color_temp, subset=["Temp (°C)", "Temp (°F)"]) import caas_jupyter_tools as tools; tools.display_dataframe_to_user(name="New York 24-Hour Forecast", dataframe=df) styled_df