Plot CSV Data in Python/v3

How to create charts from csv files with Plotly and Python

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In [1]:
import plotly


In [2]:
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.figure_factory as FF

import numpy as np
import pandas as pd

A Simple Example

CSV or comma-delimited-values is a very popular format for storing structured data. In this tutorial, we will see how to plot beautiful graphs using csv data, and Pandas. We will import data from a local file sample-data.csv with the pandas function: read_csv().

In [3]:
df = pd.read_csv('sample-data.csv')

sample_data_table = FF.create_table(df.head())
py.iplot(sample_data_table, filename='sample-data-table')
In [4]:
trace1 = go.Scatter(
                    x=df['x'], y=df['logx'], # Data
                    mode='lines', name='logx' # Additional options
trace2 = go.Scatter(x=df['x'], y=df['sinx'], mode='lines', name='sinx' )
trace3 = go.Scatter(x=df['x'], y=df['cosx'], mode='lines', name='cosx')

layout = go.Layout(title='Simple Plot from csv data',
                   plot_bgcolor='rgb(230, 230,230)')

fig = go.Figure(data=[trace1, trace2, trace3], layout=layout)

# Plot data in the notebook
py.iplot(fig, filename='simple-plot-from-csv')

Plotting Data from External Source

In the next example, we will learn how to import csv data from an external source (a url), and plot it using Plotly and pandas. We are going to use this data for the example.

In [5]:
df = pd.read_csv('')

df_external_source = FF.create_table(df.head())
py.iplot(df_external_source, filename='df-external-source-table')
In [6]:
trace = go.Scatter(x = df['AAPL_x'], y = df['AAPL_y'],
                  name='Share Prices (in USD)')
layout = go.Layout(title='Apple Share Prices over time (2014)',
                   plot_bgcolor='rgb(230, 230,230)',
fig = go.Figure(data=[trace], layout=layout)

py.iplot(fig, filename='apple-stock-prices')