Plotting power vs. rotor speed for all turbines¶

In [1]:

#import libraries
import pandas as pd
import itertools
%matplotlib inline

In [2]:

#create dataframe from csv
df=pd.read_csv('C:/Users/nithi/Google Drive/Python/Student Data/SCADA.csv',skip_blank_lines=True)

In [3]:

#create pivot table (new dataframe)
power=pd.pivot_table(df,index=['rs_av'],columns=['turbine'],values=['ap_av'])

In [4]:

#removing pivot table values name from heading
power.columns=power.columns.droplevel(0)

In [5]:

#list of column headers (i.e. turbines 1 to 25)
list1=power.columns.tolist()

In [6]:

#create new list for individual subplot titles
list2=['Average active power vs. rotor speed for turbine %s' % x for x in list1]

In [7]:

#rename index name
power.index.name='Rotor speed (rpm)'

In [8]:

#plotting all columns (i.e., turbines 1 to 25) in the same figure 
ax=power.plot(subplots=True,figsize=(50,30),layout=(5,5),style='.',sharex=False,title=list2,legend=False)
list3=list(range(0,5))
list4=list(itertools.product(list3,list3))
for (x,y) in list4:
    ax[x][y].set_ylabel('Average active power (kW)')

In [ ]: