Code Portfolio Example

Code Portfolio Example#

Looping by Index#

1-24-22#

The code below loops by index over the value of x and adds 4 to all of the values.

When I use this code, I need to change:

  • range(len(x)) (specifically, the value x) to whatever we are looping over.

  • x[gg] = x[gg]+4 To whatever procedure we want the loop to be repeating.

x = [4,12,16,22,33,49]

for gg in range(len(x)):
    x[gg] = x[gg]+4

Reading in Data Using Pandas#

1-24-22#

The code below reads in a .csv file using Pandas’s read_csv function. This should really only be used for CSV files or Excel files (using read_excel). Use Numpy’s fromfile to read in binary (.bin) or Yaff (.yaff) files.

When I use this code, I need to change:

  • data to be a more descriptive variable name.

  • dataset.csv to the name of the data file.

  • delimeter if the delimeter isn’t a comma (other delimeters include ;).

  • skiprows if there are rows at the top of the file I want to skip.

  • encoding if the encoding is something other than utf-8 (other encodings include utf-16be).

import pandas as pd

data = pd.read_csv("dataset.csv",delimiter=',',skiprows=0,encoding='utf-8')

Reading in Data Using Numpy#

1-24-22#

The code below reads in a .bin file using Numpy’s fromfile function. This works for all kinds of file types, including binary (.bin) and yaff (.yaff).

When I use this code, I need to change:

  • data to be a more descriptive variable name.

  • dataset.bin to the name of the data file.

  • dtype to be whatever the data type that this file uses (other commonly used types are float32).

import numpy as np

data = np.fromfile('dataset.bin', dtype='int32')

Making a Plot#

1-24-22#

The code below creates a plot showing x_data versus y_data.

When I use this code, I need to change:

  • x_data to whatever my x variable is.

  • y_data to whatever my y variable is.

  • label to whatever the label fo this dataset is.

  • xlabel to whatever the name of my x variable is.

  • ylabel to whatever the name of my y variable is.

  • title to whatever the title of this figure should be.

import matplotlib.pyplot as plt
%matplotlib inline

plt.plot(x_data,y_data,label="X Data")
plt.xlabel("X Data")
plt.ylabel("Y Data")
plt.title("X Vs. Y Dataset")
plt.grid()
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