CODEWITHSUNDEEP
pythonpandasmatplotlibplotdataframe
Lukasz
Lukasz

Reputation: 2606

TypeError for bar plot with custom date range

I'm attempting to display a dataframe as a bar graph with a custom date range for xlim. I'm able to output a graph if I select kind='line' but I get the following error message when attempting kind='bar': 

TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

the dataframe looks as follows:

df1 = 
     Date         Quantity
0    2010-01-01   1  
1    2010-01-02   0
2    2010-01-03   0
3    2010-01-04   2
4    2010-01-05   3
5    2010-01-06   1
6    2010-01-07   0
7    2010-01-08   1
8    2010-01-09   1
9    2010-01-10   2
10   2010-01-11   0
11   2010-01-12   5
12   2010-01-13   2
13   2010-01-14   1
14   2010-01-15   2
...

This works:

df1.plot(x='Date', y='Quantity', kind='line', grid=False, legend=False, 
         xlim=['2010-01-01', '2010-01-10'], figsize=(40, 16))

but this doesn't

    df1.plot(x='Date', y='Quantity', kind='bar', grid=False, legend=False, 
         xlim=['2010-01-01', '2010-01-10'], figsize=(40, 16))

Yet if I remove xlim from kind='bar' I produce an output. It would be nice to be able to output a bar graph with a custom x range.

Upvotes: 2

Views: 74

Answers (1)

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210842

What about an alternative approach - filtering your data before plotting?

In [10]: df.set_index('Date').ix['2010-01-01' : '2010-01-10']
Out[10]:
            Quantity
Date
2010-01-01         1
2010-01-02         0
2010-01-03         0
2010-01-04         2
2010-01-05         3
2010-01-06         1
2010-01-07         0
2010-01-08         1
2010-01-09         1
2010-01-10         2

In [11]: df.set_index('Date').ix['2010-01-01' : '2010-01-10', 'Quantity'].plot.bar(grid=False, legend=False)

Upvotes: 2

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