[FIXED] Matplotlib re-ordering y axis

Issue

Attempting to make a simple 2D matplotlib plot, but it's re-ordering the y-axis labels to keep the graph linear. How can I avoid this?

Code:

data = np.array([
    ['Jun 1', 1.2, 0.2],
    ['Jun 2', 1.3, 1.2],
    ['Jun 3', 1.4, 0.9],
    ['Jun 4', 1.1, 0.5],
    ['Jun 5', 1.6, 1.2],
    ['Jun 6', 2.2, 0.2],
    ['Jun 7', 3.4, 1.6]
])
df = pd.DataFrame(data, columns=['date', 'income', 'spent'])
plt.plot(df['income'])

I'd just like a normal graph: X axis: index Y axis: df.income (where the visual plot range is auto-calculated)

The same issue with the scatterplot:

Solution

It's because of your types. When numpy sees a string, it assumes everything in the array to be an object. So your income and spent data is actually text if you dig into the dtypes. Reconvert them before plotting:

data = np.array([
    ['Jun 1', 1.2, 0.2],
    ['Jun 2', 1.3, 1.2],
    ['Jun 3', 1.4, 0.9],
    ['Jun 4', 1.1, 0.5],
    ['Jun 5', 1.6, 1.2],
    ['Jun 6', 2.2, 0.2],
    ['Jun 7', 3.4, 1.6]
])

df = pd.DataFrame(data, columns=['date', 'income', 'spent'])

for c in ['income', 'spent']:
    df[c] = df[c].astype(float)

plt.plot(df['income'])

or (better practice):

data = [
    ['Jun 1', 1.2, 0.2],
    ['Jun 2', 1.3, 1.2],
    ['Jun 3', 1.4, 0.9],
    ['Jun 4', 1.1, 0.5],
    ['Jun 5', 1.6, 1.2],
    ['Jun 6', 2.2, 0.2],
    ['Jun 7', 3.4, 1.6]
]

df = pd.DataFrame(data, columns=['date', 'income', 'spent'])

plt.plot(df['income'])

Answered By - fishmulch