plotting data from columns from the same dataframe in pandas

Question

I have a dataframe with 60 columns of data (column 1 = I 1, column 2 = S 1.... column 3 = I 2, column 4 =S 2.. and so on)...

I want to create a function that selects two columns at a time for slicing, plotting and finding the integral of the slice. I can do this for two columns but I don't know how to implement a function to run all 60 columns. So far I have the following:

df = pd.DataFrame.from_csv(filepath, index_col =None)
df_slice =df.iloc[23500:25053]


R = df_slice['I 1']
I = df_slice['S 1']
rcParams['figure.figsize']= 10,5
plt.plot(R, I)
plt.xlabel('cm-1')
plt.ylabel('Hz')

#integration of peak

area = trapz(R)
print area

for the function:

def integrate_peak(filepath):
    df = pd.DataFrame.from_csv(filepath, index_col =None)
    for row in df:
        ..........slice
        ..........overlay plots
        ..........get integral for each plot curve

output:

30 integral answers in a separate dataframe

Any help would be appreciated.

EDIT:

I've tried this:

def get_slice():
    df = pd.DataFrame.from_csv(filepath, index_col =None)
    for i in range(1,31):
        df_slice = df.iloc[23500:25053]
        R = df_slice['I %i' %i]
        I = df_slice['S %i' %i]
        plt.plot(R,I)
        area = trapz(R)
        print area

get_slice()

This gives me an overlay of 30 plots, however gives me 30 values for integral (all being the same number)

Answer 1

Something like:

def f(col1,col2):
    print col1,col2
    R = df[col1]
    I = df[col2]
    rcParams['figure.figsize']= 10,5
    plt.plot(R, I)
    plt.xlabel('cm-1')
    plt.ylabel('Hz')
    area = np.trapz(R)
    print area
    return col2
reduce(lambda x,y:f(x,y),df)
plt.show()

For processing (col1,col2) then (col2,col3) and so on.

Answer 2

Alas, i have found the solution.

def get_slice():
        area_list = []
        df = pd.DataFrame.from_csv(filepath, index_col =None)
        Raman = df['I 1']
        Intensity = df['S 1']

        for i in range(1,31):
            df_slice = df.iloc[23500:25053]
            R = df_slice['I %i' %i]
            I = df_slice['S %i' %i]
            for i in R:
                area = trapz(R, x = I)
            area_list.append(area)
        a = np.mean(area_list)