Creating bar plot with frequency distribution based

Question

I have a dataframe with this kind of structure:

ID | Size | Value 1 | 1 | 10 2 | 2 | 20 3 | 1 | 10 4 | 1 | 10 5 | 1 | 15 6 | 1 | 12 7 | 1 | 20 

I want to create bar plot of the distribuition of column "Values" when the "Size" column is equal to 1.

With the current example:

1. the x-axis should have: 10, 12, 15 and 20
2. the y-axis should have 1 (for the 12, 15 and 20) and 3 for the 10

I don't have a lot of code. Basically I just created a new dataframe with only the rows where Size=1 and then performed value_counts():

data1 = data.loc[(data['Size'] == 1)] count = data1['Value'].value_counts() 

The variable count now has a Series object with a Value and a counter.

How can I split the value of count in order to have two lists (values and counters) to send to the plotting code?

Answer 1

What you are looking for is a histogram. It plots the distribution of a given series of values. So, you can just extract the values that you want to plot from your dataframe and then use matplotlib's histogram function. Here is the code:

import matplotlib.pyplot as plt to_plot = data.loc[df['Size']==1]['Value'] plt.hist(to_plot) plt.show() 

This is the output I get, note that I haven't done any formatting, this is just the raw output.

The above option is more flexible. But in your case you can also use the following:

import matplotlib.pyplot as plt to_plot = data.loc[df['Size']==1]['Value'] to_plot.value_counts().plot.bar() 

Answer 2

You can use hist from matplotlib library

import matplotlib.pyplot as plt plt.hist( data['Value'] ) plt.show()