I have a data frame table "pandastable3" that looks like this:
I would like to plot histograms of values for all the columns separately, but so far I am able to get only a single figure containing all the plots together with this to plot the first 3 columns:
pandastable3.hist(layout=(1,2,3))
But I am not sure I am doing that correctly as I cannot visualize anything.
I suppose diff() gives different plots for each column:
pandastable3.diff().hist()
Related
I currently have a dataframe called df with 18 columns, and I have plotted a histogram of each to check the distribution shape of each variable using the hist() function in pandas:
df.hist(figsize=(30,30))
What I now want to do is add a boxplot above each box plot so I can understand at a glance which variables contain outliers. I want the plot to look as follows:
I can plot the boxplot using the following code, but it displays all of the boxplots on a single plot:
df.boxplot(figsize=(30,30))
And I can add a group by, however, this isn't what I require. I just want each histogram in my df.hist plot to be overlayed with the boxplot derived from the same column of data. I suspect I could write a funciton to do this, but as the hist function seems quite intuitive, I suspect there is a straighforward way that I'm probably missing.
I am trying to plot a line graph that shows multiple lines within my dataframe as the separate lines for comparison i.e. having one as the 'expected' and another to show variations. Additionally, I'm trying to show the columns as the xticks and percentages as the y values:
What I'm trying to show is row 1 as the 'expected' percent and then be able to use any other row i.e. food, bakery products, etc. to show any deviation for that across all columns (serving as the x-axis). I hope that this make sense and any help is appreciated!! I'm a new coder going through a bootcamp.
I have a pandas dataframe with two columns and around 50 rows. I want to create a scatter plot of the two columns but I also want to have the datapoints connected to each other. So I did something like this:
plt.plot(df['colA'], df['colB'], 'o-')
plt.show()
I am getting an output like this:
But I want to have data points connected to each other so as to give an ellipse circumscribing the data points. I feel like the reason I'm getting this plot is that in the dataframe that's how the datapoints are sequenced.
Is there a way to deal with this?
Any help would be appreciated!
Thanks in advance
I've got a large dataframe and each row has a count of the number of good, okay, bad and other events against it.
I'm trying to replace those 4 columns with a single column that visually represents the same data. i.e. I'd like to replace 4 cells with a single cell containing a stacked horizontal bar
So I want my table to look like the above rather than the like the bottom
I've struggling with the python thus far as the only route I can think of combining them would be to generate each bar seperately in matplotlib, export to jpg and then import into the dataframe.
Which feels like it won't be scaleable...
Any suggestions?
I'm facing a problem to plot 2 box plots into a same graph to make easier to compare them.
The problems is that each box plot comes from a different dataframe with different lenght, however, both have same columns.
My two data frame are:
'headlamp_water' and 'headlamp_crack'; the column I want to use is called 'Use Period'.
How do I do it?
Any help will be highly appreciated
You can concat() the columns and call the boxplot() method.
pd.concat([headlamp_water['Use Period'], headlamp_crack['Use Period']], axis=1).boxplot()
Using axis=1, you select the columns.