I’ve got pandas DataFrame, df, with index named date and the columns columnA, columnB and columnC
I am trying to scatter plot index on a x-axis and columnA on a y-axis using the DataFrame syntax.
When I try:
df.plot(kind='scatter', x='date', y='columnA')
I ma getting an error KeyError: 'date' probably because the date is not column
df.plot(kind='scatter', y='columnA')
I am getting an error:
ValueError: scatter requires and x and y column
so no default index on x-axis.
df.plot(kind='scatter', x=df.index, y='columnA')
I am getting error
KeyError: "DatetimeIndex(['1818-01-01', '1818-01-02', '1818-01-03', '1818-01-04',n
'1818-01-05', '1818-01-06', '1818-01-07', '1818-01-08',n
'1818-01-09', '1818-01-10',n ...n
'2018-03-22', '2018-03-23', '2018-03-24', '2018-03-25',n
'2018-03-26', '2018-03-27', '2018-03-28', '2018-03-29',n
'2018-03-30', '2018-03-31'],n
dtype='datetime64[ns]', name='date', length=73139, freq=None) not in index"
I can plot it if I use matplotlib.pyplot directly
plt.scatter(df.index, df['columnA'])
Is there a way to plot index as x-axis using the DataFrame kind syntax?
Answers:
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Method 1
This is kind of ugly (I think the matplotlib solution you used in your question is better, FWIW), but you can always create a temporary DataFrame with the index as a column usinng
df.reset_index()
If the index was nameless, the default name will be 'index'. Assuming this is the case, you could use
df.reset_index().plot(kind='scatter', x='index', y='columnA')
Method 2
A more simple solution would be:
df['x1'] = df.index
df.plot(kind='scatter', x='x1', y='columnA')
Just create the index variable outside of the plot statement.
Method 3
At least in pandas>1.4 whats easiest is this:
df['columnA'].plot(style=".")
This lets you mix scatter and line plots, as well as use the standard pandas plot interface
All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0