Accessing Elements in DataFrames¶

This lesson covers:

Assessing specific elements in Pandas Series and DataFrames

Accessing elements in an array or a DataFrame is a common task. To begin this lesson, clear the workspace set up some vectors and a $5\times5$ array. These vectors and matrix will make it easy to determine which elements are selected by a command.

Start by creating 2 DataFrame and 2 Series. Define x=np.arange(24).reshape(5,5) which is a 5 by 5 array and y=np.arange(5) which is a 5-element 1-d array. We need:

x_df: A default DataFrame containing x
x_named: A DataFrame containing x with index "r0", "r1", ..., "r4" and columns "c0", "c1", ... "c4".
y_s: A default Series containing y
y_named: A Series containing y that has the index "r0", "r1", ..., "r4"

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Problem: Selecting a row by name¶

Select the 2nd row of x_name using .loc.

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Problem: Selecting a column by name¶

Select the 2nd columns of x_name using both [] and .loc.

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Problem: Selecting a elements of a Series by name¶

Select the 2nd element of y_name using both [] and loc.

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Problem: Selecting rows and columns by name¶

Select the 2nd and 4th rows and 1st and 3rd columns of x_name.

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Problem: DataFrame selection with default index and column names¶

Select the 2nd and 4th rows and 1st and 3rd columns of x_df.

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Problem: Series selection with the default index¶

Select the final element in y_s

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Problem: Subseries selection¶

Select the subseries of y_named and y_s containing the first, fourth and fifth element.

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Load the data in momentum.csv.

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# Setup: Load the momentum data

import pandas as pd

momentum = pd.read_csv("data/momentum.csv", index_col="date", parse_dates=True)
momentum.head()

Problem: Selecting data on a single day¶

Select returns on February 16, 2016.

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Problem: Selecting data in a single month¶

Select return in March 2016.

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Problem: Selecting data in a single year¶

Select return in 2016.

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Problem: Selecting data in a date range¶

Select returns between May 1, 2016, and June 15, 2016.

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Exercises¶

Exercise: Subset time-series¶

Select the data for May 2017 for momentum portfolios 1 and 10.

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Exercise: Select using Months¶

Using a slice of YYYY-MM, select the returns for momentum portfolio 5 in the final 6 months of 2016 as Series

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Exercise: Ensure DataFrame¶

Repeat the previous problem but ensure the selection is a DataFrame.

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