Question
In Pandas, can we compare the values of two columns in the same dataframe?
Answer
Yes, you can compare values of different columns of a dataframe within the logical statement.
Say for example, you had data that stored the buy price and sell price of stocks in two columns. If you wanted to select rows of the data for which the buy price was less than the sell price, you could compare their values in the logical statement.
Example
# This logical statement is comparing
# the values of column `buy_price`
# and column `sell_price`
gains = df[df.buy_price < df.sell_price]
7 Likes
I found the above question & answer very usuful.
So, I tried based on lesson’s data to find the months for which visits in eastern clinics are less than those in western.
The expected output should be the data for March, April, May, June
I wrote:
less_east_relation_to_west =
df[df.‘clinic_east’ < df.‘clinic_west’]
print(less_east_relation_to_west)
Nevertheless, there was no output. The same happened even when I rewrote the code without ’ ’ in the name of the columns (clinic).
What was wrong with my code?
Hey @jminer583,
Try writing the column name without ‘’ .
less_east_relation_to_west =
df[df.clinic_east < df.clinic_west]
print(less_east_relation_to_west)
The above code works fine. and show the output given below.
month clinic_east clinic_north clinic_south clinic_west
2 March 81 96 65 96
3 April 80 80 54 180
4 May 51 54 54 154
5 June 112 109 79 129
1 Like
df[df.‘clinic_east’ < df.‘clinic_west’]
You don’t need the single inverted commas in the above piece of your code. Without those, it should work fine.
@jminer583 What I noticed is that on Codecademy it doesn’t produce any output. But if you copy the same exact code and run it on Jupyter Notebook, it runs. You don’t need the quotation marks around the column names.
