Python Forum

I've been battling this one for over an hour so I'm going to ask for help.

I have a dataframe column that shows trade results. I want those less than zero to plot red and nonnegative values to plot green. I saw this on SO:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(10)
y = np.arange(10) * 0.1

mask1 = y < 0.5
mask2 = y >= 0.5

plt.bar(x[mask1], y[mask1], color = 'red')
plt.bar(x[mask2], y[mask2], color = 'blue')
plt.show()

Here's my attempt:

plt.figure(figsize=(15, 10))
mask1 = summary_results['ROI%'] < 0
mask2 = summary_results['ROI%'] >= 0
plt.bar(summary_results.index,summary_results['ROI%'][mask1],color = 'r')
plt.bar(summary_results.index,summary_results['ROI%'][mask2],color = 'g')
plt.grid()
plt.show()

This gives ValueError: shape mismatch: objects cannot be broadcast to a single shape .

I think the problem is the number of values either negative or nonnegative are less than the number of total values, which is conveyed by summary_results.index. I'm really not sure what to do with the x-argument. I don't really want to bring the whole index in using this approach--just the index values corresponding to the negative or nonnegative ROI% values, accordingly, as the position for the bar to be plot.

Really, I just want to go down the summary_results['ROI%'] column and plot a bar for each value. I originally thought default would be left to right, but that gave TypeError with one positional argument missing.

Another way I thought of doing this was to have color = colors where colors is a list of 'r' and 'g' depending on whether summary_results['ROI%'] is negative or nonnegative. Seems like I could do this with a list comprehension, but I'm not quite sure how to do it. I can't say if summary_results['ROI%'] < 0 because summary_results['ROI%'] is a dataframe column (Series?) and it doesn't make sense to evaluate a whole series against one value. I really mean to iterate down the series and evaluate each value. So maybe this could be done with a for loop?

colors = []
for i in summary_results['ROI%']:
    if i < 0:
        colors.append('r')
    else:
        colors.append('g')

This could work, but it seemed like the list comprehension would be simpler.

And the mask idea seems nifty... any way to make that work?

This works for the mask approach:

plt.figure(figsize=(15, 10))
mask1 = summary_results['ROI%'] < 0
mask2 = summary_results['ROI%'] >= 0
plt.bar(summary_results.index[mask1],summary_results['ROI%'][mask1],color = 'r')
plt.bar(summary_results.index[mask2],summary_results['ROI%'][mask2],color = 'g')
plt.grid()
plt.show()

Mark17

Mark17