Python code to multiply two columns and then create new column with values

Question

I am making a python code that first averages minute data into hourly data. I then want to multiply the values in the two columns in the hourly data and create a new column with the multiplied values. I am stuck on the multiplication step.

import pandas as pd
import numpy as np

df = pd.read_csv("inputfile.csv", index_col="DateTime", parse_dates=True)
df = df.resample('1H').mean()
df = df.reindex(pd.date_range(df.index.min(), df.index.max(), freq="1H"))
df.to_csv('outputfile.csv', index=True, index_label="DateTime")

Data from hourly averages

DateTime        current     voltage
11/1/2014 0:00  3.366184207 12.1758535
11/1/2014 1:00  3.361604775 12.1827364
11/1/2014 2:00  3.358049691 12.17596822
11/1/2014 3:00  3.354833198 12.1827364
11/1/2014 4:00  3.361096907 12.1827364
11/1/2014 5:00  3.361096907 12.1827364
11/1/2014 6:00  3.366344918 15.72258904
11/1/2014 7:00  3.419681019 1495.925115
11/1/2014 8:00  3.663316184 1870.538086
11/1/2014 9:00  4.369056237 1925.408667
11/1/2014 10:00 4.404945809 1938.888254
11/1/2014 11:00 4.711192238 1994.759897
11/1/2014 12:00 4.82263279  1995.281601
11/1/2014 13:00 4.428242773 1961.089536
11/1/2014 14:00 4.038091129 1895.686707
11/1/2014 15:00 4.04098199  1904.352924
11/1/2014 16:00 3.748518044 1852.646768
11/1/2014 17:00 3.397967499 1554.434254
11/1/2014 18:00 3.371380174 56.24243593
11/1/2014 19:00 3.375613815 12.18733199
11/1/2014 20:00 3.369686692 12.18239812
11/1/2014 21:00 3.367993271 12.18351949
11/1/2014 22:00 3.374089682 12.17048603
11/1/2014 23:00 3.367485231 12.18946266

I would like to multiply the current column by voltage column and create a new column with those values.

did you try df['current'] * df['voltage']?

EdChum
– EdChum

2017-02-24 16:47:48 +00:00
Commented Feb 24, 2017 at 16:47 — EdChum
– EdChum, Commented Feb 24, 2017 at 16:47

Chirag · Accepted Answer · 2017-02-24 16:49:02Z

11

You can try something like this:

df['Power'] = df['current']*df['voltage']

answered Feb 24, 2017 at 16:49

Chirag

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8 Comments

acb Over a year ago

this works however is there anyway to write this without typing in the column header and just use the column number to multiply.

AsheKetchum Over a year ago

@acb what do you mean?

acb Over a year ago

sorry kind of confusing to word by my actual data has about 10 columns for current. I would like to multiply each column by the voltage and create 10 new columns for power.

AsheKetchum Over a year ago

@acb do you have multiple columns named 'current'?

ijoseph Over a year ago

@BFurtado just do df.loc[:, 'Power'] = ... instead.

|

AsheKetchum · Accepted Answer · 2017-10-02 14:51:14Z

8

df[newcolumn] = df['current']*df['voltage']
will work.
You can name provide newcolumn as a variable.

def getPower(df, newColumn, numOfCol):
    for i in range(numOfCol):
        current = 'current#%d' % (i+1)
        voltage = 'voltage#%d' % (i+1)
        power   = 'power#%d' % (i+1)
    df[power] = df[current]*df[voltage]

getPower(df, 'Power', numOfCols) would create the column.

EDIT: This will work if you named your current columns like 'current1', current2',...

edited Oct 2, 2017 at 14:51

answered Feb 24, 2017 at 16:50

AsheKetchum

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2 Comments

Bowen Liu Over a year ago

Just saw this. Could you help me understand what #%d is and what can is the 'current#%d' % (i+1) step doing please?

Adav Over a year ago

%d (%s for string ) is to mark the place you want to insert a decimal value in a string. The current method is "sometring {}".format(obj_to_insert)

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