Matplotlib mangled line graphs when using datetime data on x axis

Question

When using matplotlib to graph time series data, I get strange mangled outputs

This only happens when I convert the time series string in the csv to a datetime object. I need to do this conversion to make use of Matplotlib's time series x axis labelling.

abc = pd.read_csv(path + "Weekly average capacity factor and demand - regular year" + ".csv", parse_dates=True, index_col="Month", header=0)

fig, ax = plt.subplots()

x = abc.index
y1 = abc["Wind"]

curve1 = ax.plot(x, y1)

pd.read_csv(parse_dates=True) creates the index as a datetime64[64] object. Perhaps this isn't optimized for use by matplotlib?? How can I make this work.

Post a portion of yourself csv file in a code block so we can test your code with your data. — pakpe
– pakpe, Commented Feb 5, 2021 at 0:26

goalie1998 · Accepted Answer · 2021-02-05 00:45:38Z

1

Your date index is not in order. Matplotlib does not sort the data prior to plotting, it assumes list order is the data order and tries to connect the points (You can check this by plotting a scatter plot and your data will look fine). You have to sort your data before trying to plot it.

abc = pd.read_csv(path + "Weekly average capacity factor and demand - regular year" + ".csv", parse_dates=True, index_col="Month", header=0)

x, y1 = zip(*sorted(zip(abc.index, abc["Wind"])))

fig, ax = plt.subplots()
curve1 = ax.plot(x, y1)

answered Feb 5, 2021 at 0:45

goalie1998

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