Simple Mathematics Operations in Python/v3

Learn how to perform simple mathematical operations on dataframes such as scaling, adding, and subtracting

Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.

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Imports¶

The tutorial below imports NumPy, Pandas, and SciPy.

In [1]:

import plotly.plotly as py
import plotly.graph_objs as go
from plotly.tools import FigureFactory as FF

import numpy as np
import pandas as pd
import scipy

Import Data¶

Let us import a timeseries dataset to perform mathematical operations on:

In [2]:

data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/timeseries.csv')

table = FF.create_table(data)
py.iplot(table, filename='timeseries-data-table')

Out[2]:

Scale a Dataset¶

You can modify a dataset by scaling each number by a constant.

In [3]:

x = data['Date']
y = data['A']
y2 = [2.*k for k in y]

trace1 = go.Scatter(
    x=x,
    y=y,
    mode='markers',
    name='Data',
    marker=dict(
        size=12
    )
)

trace2 = go.Scatter(
    x=x,
    y=y2,
    mode='markers',
    name='Scaled by 2',
    marker=dict(
        size=12,
        symbol='x'
    )
)

trace_data = [trace1, trace2]
py.iplot(trace_data, filename='scale-a-dataset')

Out[3]:

Subtract Two Columns¶

In [4]:

trace1 = go.Scatter(
    x=data['Date'],
    y=data['A'],
    mode='markers',
    name='Column A',
    marker=dict(
        size=12
    )
)

trace2 = go.Scatter(
    x=data['Date'],
    y=data['D'],
    mode='markers',
    name='Column D',
    marker=dict(
        size=12
    )
)

trace3 = go.Scatter(
    x=data['Date'],
    y=data['D'] - data['A'],
    mode='markers',
    name='Column D - Column A',
    marker=dict(
        size=12,
        symbol='square-open'
    )
)

trace_data1 = [trace1, trace2, trace3]
py.iplot(trace_data1, filename='subtract-two-dataframe-columns')

Out[4]:

Modify DataFrame Entries¶

Use arithmetic operations including addition, subtraction, multiplication and division to change the values in a DataFrame column:

In [5]:

dataframe = pd.DataFrame([[1, 2],
                          [3, 4],
                          [5, 6],
                          [7, 8]],
                         columns=['A', 'B'])

table = FF.create_table(dataframe)
py.iplot(table, filename='math-operations-dataframe')

Out[5]:

In [6]:

dataframe['A'][0] = 120
dataframe['B'][3] = -2*dataframe['B'][3]

table = FF.create_table(dataframe)
py.iplot(table, filename='math-operations-dataframe-changed')

Out[6]: