In this last entry on Python plotting libraries, we will review Bokeh, a library for plotting interactive graphics based on HTML/JS. These plots can then be used in a web application or website to display results.

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# data science

# Drawing plots with Pandas

StandardIn this new entry, we will see the plotting capabilities of Pandas and how to mix it with Matplotlib.

# Decorating graphics with Matplotlib

StandardIn the last entry, we saw a brief introduction to Matplotlib by drawing three basic graphic types (a line plot, a bar chart and pie chart). But the resulting graphics were arguably unattractive.

# Introduction to Matplotlib

StandardIn the previous entry, we introduced the libraries available for graphing in Python. In this entry, we will have a very basic look on the first proposed library, Matplotlib. We will create three types of graphics: a line plot, a bar chart and a pie chart.

# Analyzing trends in data with Pandas

StandardA very important aspect in data given in time series (such as the dataset used in the time series correlation entry) are trends. Trends indicate a slow change in the behavior of a variable in time, in its average over a long period.

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# Correlating time series with Pandas

StandardIn this entry, we will see a practical application of the Pandas library. We will use a DataFrame where we will load the contents of a CSV file containing data of measurements on a flotation cell.

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# Loading a DataFrame from an SQL database

StandardIn a prior entry we described how to load data from a CSV file. In this entry, we will do a quick introduction on how to load the contents of an SQL table into a DataFrame.

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# Reading and writing CSV files with Pandas

StandardCSV (Comma Separated Values) files are a very simple and common format for data sharing. CSV files are simple (albeit sometimes large) text files that contain tables. Each line is a row, and within each row, each value is assigned a column by a *separator*.

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# Pandas DataFrame

StandardIn the previous entry, I introduced Pandas Series. I also compared it with the column of an Excel workbook. Well, following that analogy, DataFrame is the full Excel workbook, where each column is … you guessed it; a Series.

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# Pandas Series

StandardIn this entry, I will quickly introduce the Series. It is the most simple structure provided by Pandas, and it can be thought of as a column in an excel spreadsheet.

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