dates_dist_plot (df:pandas.core.frame.DataFrame, col:str, sampling_period:str='W-MON', ax:Union[ForwardRef('Extens ionArray'),numpy.ndarray,ForwardRef('Index'),ForwardRef( 'Series'),list,range,NoneType]=None, date_col:str='collection_date', ylim:Optional[Tuple[float,float]]=None, quantiles:Optional[List[Tuple[float,str]]]=None)
*Creates a scatter plot of data points and their statistics based on a specified sampling period.
Args: df (pd.DataFrame): The input DataFrame containing the data. col (str): The column name in the DataFrame to plot. sampling_period (str, optional): The frequency to resample the data. Defaults to ‘W-MON’. ax (Optional[Axes], optional): A matplotlib axes object to plot on. Defaults to None. date_col (str, optional): The name of the date column in the DataFrame. Defaults to ‘collection_date’. ylim (Optional[Tuple[float, float]], optional): A tuple defining the y-axis limits. Defaults to None. quantiles (Optional[List[Tuple[float, str]]], optional): A list of tuples containing quantiles and their labels. Defaults to [(0.1, “10%”), (0.9, “90%”)].*
data = generate_synthetic_data()
data.head()| date_of_research_stage | age_at_research_stage | sex | val1 | val2 | |
|---|---|---|---|---|---|
| participant_id | |||||
| 0 | 2022-12-01 | 57.777073 | 1 | 150.216212 | 56.936487 |
| 1 | 2020-07-29 | 53.770724 | 1 | 117.603875 | 47.152785 |
| 2 | 2020-09-30 | 51.326393 | 1 | 97.928950 | 41.250308 |
| 3 | 2022-05-06 | 61.217276 | 0 | 105.169939 | 41.422605 |
| 4 | 2021-06-29 | 45.835170 | 0 | 54.735540 | 26.292285 |
dates_dist_plot(data, col="val1", date_col="date_of_research_stage")