I have this code where the loop iterates through PRDCT column then calculates the p and r value, and creates a graph for each unique product code:
for prd in df_final.PRDCT.unique():
df_tmp = df_final[df_final.PRDCT== prd].reset_index().copy()
coeff, p = pearsonr(df_tmp['PRDCT_mean'], np.arange(0,len(df_tmp['PRDCT_mean'])))
plt.figure(figsize = (15,6))
plt.plot(df_tmp['Month'],df_tmp['PRDCT_mean'], marker="o")
plt.title(prd, fontsize=18)
plt.ylabel('PRDCT_mean')
plt.xlabel('Month')
plt.grid(True)
plt.ylim((-60,60))
plt.xticks(rotation= 'vertical',size=8)
plt.show()
Question 1 : How can I show the respective coefficient value of each unique product code beside the graph title of the each product?
Question 2 : How can I save the result of each pearsonr P and r value that takes place in for each iteration seperately?
Prefer these actions to include in the same code if possible
Thanks in adv
Consider creating a defined method that handles all steps: builds plot, concatenates string statistics to title, and returns statistics. Then create a dictionary via comprehension using DataFrame.groupby
.
def run_plot_save_stats(prd, df_tmp):
df_tmp = df_tmp.reset_index().copy()
coeff, p = pearsonr(df_tmp['PRDCT_mean'], np.arange(0,len(df_tmp['PRDCT_mean'])))
title = f"Product: {prd} - pearson coeff: {coeff.round(4)} p-value: {p.round(4)}"
plt.figure(figsize = (15,6))
plt.plot(df_tmp['Month'],df_tmp['PRDCT_mean'], marker="o")
plt.title(title, fontsize=18)
plt.ylabel('PRDCT_mean')
plt.xlabel('Month')
plt.grid(True)
plt.ylim((-60,60))
plt.xticks(rotation= 'vertical',size=8)
plt.show()
return {"pearson": coeff, "p_value": p}
prod_stats_dict = {
grp: run_plot_save_stats(grp, df) for grp, df in df_final.groupby("PRDCT")
}
prod_stats_dict["product1"]["pearson"]
prod_stats_dict["product1"]["p_value"]
prod_stats_dict["product2"]["pearson"]
prod_stats_dict["product2"]["p_value"]
...