how to use 'for' loop to create multiple figures, not all data in one figure?-CodePudding

I want to plot some statistics results for each region. I have nested 'for' loops, where in the inner loop it generates the statistics, in the outer loop it selects the regions and plot the respective statistic results. Not sure why my code plots data from all regions into the same figure, not one figure for a region.

Yrstat = []
for j in Regionlist:
    for i in Yrlist:
            dfnew = df.loc[(df['Yr']==i)&(df['Region']==j)]
            if not dfnew.empty:
                #calculate the confidence interval and mean for data in each year
                CI = scipy.stats.norm.interval(alpha=0.95, loc=np.mean(dfnew['FluxTot']), scale=scipy.stats.sem(dfnew['FluxTot']))
                list(CI)
                mean = np.mean (dfnew['FluxTot'])
                Yrstat.append((i, mean, CI[0], CI[1]))
        
    #convert stats list to a dataframe
    yrfullinfo = pd.DataFrame(Yrstat, columns = ['Yr', 'mean', 'CI-','CI '])

    #making figures
    fig, ax =plt.subplots()
    ax.plot(yrfullinfo['Yr'], yrfullinfo['mean'], label = 'mean')
    ax.plot(yrfullinfo['Yr'], yrfullinfo['CI-'], label = '95%CI')
    ax.plot(yrfullinfo['Yr'], yrfullinfo['CI '], label = '95%CI')
    ax.legend()
   
    #exporting figures
    filename = "C:/Users/Christina/Desktop/python test/Summary in {}.png". format (j)
    fig.savefig(filename)
    plt.close(fig)

CodePudding user response：

The problem wasn't the figure, the script saves a png file for each region in an own plot which is correct. The problem is your data. You intitialize Yrstat=[] outside of both loops. Then you append data to it in every step of the inner loop (and also all outer loops) and plot the data of the "new" DataFrame yrfullinfo. This DataFrame grows bigger with each iteration. You need to create a new list of values for each Region, that's why I moved the list Yrstat in the outer loop to get reinitialized for every region.

for j in Regionlist:    
    Yrstat = []
    for i in Yrlist:
        dfnew=dfmerge.loc[(dfmerge['Yr']==i)&(dfmerge['Region']==j)]
        if not dfnew.empty:
            #get all statistics for data in each year
            CI = st.norm.interval(alpha=0.95, loc=np.mean(dfnew['FluxTot']), scale=st.sem(dfnew['FluxTot']))
            list(CI)
            mean = np.mean (dfnew['FluxTot'])
            Yrstat.append((j, i, mean, CI[0], CI[1]))