Previously, we read in CSV data and summarised it. Here, we will learn how to locate data using labels and tabulate categorical data. The CSV file data_pandas.csv (available here) contains simulated data of age, height and score from 20 subjects. Read in and store the CSV data in the dataframe df, using the header names. Also create and assign subjects
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Previously, we used Pandas to read and write data to CSV files, reshape data from wide to long format, and used the Seaborn package to plot paired data. Here, we will summarise some data and write the results to a CSV file. The CSV file data_pandas.csv (available here) contains simulated data of age, height and score from 20 subjects. To
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Pandas (i.e. panel data) is a Python library designed to manipulate data in tables and time series. Pandas uses many Numpy library functions to manipulate data stored in dataframes, analogous to a spreadsheet or table. Let’s look at some basic Pandas functions to manipulate data, and plot the data using the Seaborn plotting package. To begin, import libraries and simulate
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In programming, for loops are used to automate repetitive tasks, such as analysing similar datasets from different subjects. Sometimes, a dataset might be slightly different to another such that the data can be used but needs to be analysed differently in the loop. For example, data might have been accidentally sampled at a higher rate, or a nested trial needs
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Spike2 is a piece of software written by the folks at CED (Cambridge Electronic Design) to collect data with their data acquisition boards. As pointed out in a previous post, Spike2 can be used to analyse data. However, the drop-down menus and options make it difficult to ensure processing is consistent from session to session. Spike2 comes with its own
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Suppose you have some big data files to analyse, and you would like to know roughly how long it takes to run the analysis. This is so that in future, if you had to re-run the analysis, you could gauge that it will take long enough to go get a coffee or work on another job while you wait for
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