median_per_ decile.py

# lower bound for the first quantile
previous_q = 0
# store the medians in a dictionary
row = {}
# column name to calculate the quantiles from
colname = "bedrag"

for q in range(1,11):

    # .quantile() wants a decimal between 0 and 1
    q = q/10

    # calculate the quantile
    quantile = df[colname].quantile(q)

    if q < 1:
    # calculate the median of the percentile, lower than the current percentile, but larger than the previous one
        quantile_range = df.loc[(df[colname] < quantile) & (df[colname] > previous_q), "bedrag"]
    # if calculating the first decile, get only the upper bounds
    elif q == 1:
        quantile_range = df.loc[(df[colname] > previous_q), colname]

    # get median from the range
    quantile_median = quantile_range.median()

    # add it to the dictionary
    row[f"{q}-median"] = quantile_median
    
    # save this quantile the lower bound for the next quantile
    previous_q = quantile