ValueError: Wrong number of items passed 500, placement implies 1, Python and Pandas
Question: I'm importing just two columns from .xlsx file and I would like to calculate
some stuff (mean, deviation, percent change) and then I would like to plot all
this. First part doesn't give me any problems, but plotting does.

My code looks like this:

    
    
    import matplotlib.pyplot as plt
    import numpy as np
    import pandas as pd
    import matplotlib.mlab as mlab
    import math
    
    df = pd.read_excel('KDPrviIzbor.xlsx', sheetname='List1', index_col = 0)
    ch = df.pct_change(periods=252)
    
    ma = np.mean(ch)*100
    std = np.std(ch)*100
    
    x = np.linspace(-100,100,500)
    plt.plot(x,mlab.normpdf(x,ma,std))
    
    plt.show()
    

But when I run my code, I get this error:

    
    
    Traceback (most recent call last):
    File "C:/Users/David/PythonStuff/normal_distribution.py", line 21, in <module> plt.plot(x,mlab.normpdf(x,ma,std))
    File "C:\Python27\lib\site-packages\matplotlib\mlab.py", line 1579, in normpdf return 1./(np.sqrt(2*np.pi)*sigma)*np.exp(-0.5 * (1./sigma*(x - mu))**2)
    File "C:\Python27\lib\site-packages\pandas\core\ops.py", line 534, in wrapper dtype=dtype)
    File "C:\Python27\lib\site-packages\pandas\core\series.py", line 220, in __init__ data = SingleBlockManager(data, index, fastpath=True)
    File "C:\Python27\lib\site-packages\pandas\core\internals.py", line 3383, in __init__ ndim=1, fastpath=True)
    File "C:\Python27\lib\site-packages\pandas\core\internals.py", line 2101, in make_block placement=placement)
    File "C:\Python27\lib\site-packages\pandas\core\internals.py", line 77, in __init__ len(self.values), len(self.mgr_locs)))
    ValueError: Wrong number of items passed 500, placement implies 1`
    

I figured that the problem is in:

`plt.plot(x,mlab.normpdf(x,ma,std))`

but I cannot solve it. Any suggestions?


Answer: `ma` and `std` are `pandas.Series` objects in your example. The reason is,
that `np.mean` applied to a `pandas.DataFrame` returns a `pandas.Series`.
However, mlab.normpdf(x,ma,std) expects float values or numpy arrays as
inputs. You could simply convert `ma` and `std` to floats by `ma = float(ma)`.
I would not suggest to use `int(ma)` as you pointed out in your comment,
because that would cut away the decimals.

