I am trying to convert pandas dataframe bar plot to matplotlib OO concept.
(npy_dataframe["Complaint Type"].value_counts()).head().plot(kind="bar")
this live perfectly working and generating bar chat attached
now this is my OO matplotlib trying to convert below what is wrong I am doing?
%matplotlib inline
fig = plt.figure() # creates a figure
fig, ax = plt.subplots(figsize=(10,6))
#print(plt.style.available)
plt.style.use("seaborn-whitegrid")
# most frequest complaint
ax.bar(npy_dataframe["Complaint Type"].value_counts().head())
# add some label and title
ax.set(title="Most Common Compalints", ylabel="No of Complaints", xlabel="Complaint Type")
# Make the legebd visible
# ax.legend().set_visible(True)
# Add title to the figure
fig.suptitle("Compalints Analysis", fontsize=16, fontweight="bold")
# Add a mean line
ax.axhline(y=npy_dataframe["Complaint Type"].value_counts().head().mean(),linestyle="--")
Error is :-
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-25-2cbbdac7a93f> in <module>
5 plt.style.use("seaborn-whitegrid")
6 # most frequest complaint
----> 7 ax.bar(npy_dataframe["Complaint Type"].value_counts().head())
8 # add some label and title
9 ax.set(title="Most Common Compalints", ylabel="No of Complaints", xlabel="Complaint Type")
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\__init__.py in inner(ax, data, *args, **kwargs)
1445 def inner(ax, *args, data=None, **kwargs):
1446 if data is None:
-> 1447 return func(ax, *map(sanitize_sequence, args), **kwargs)
1448
1449 bound = new_sig.bind(ax, *args, **kwargs)
TypeError: bar() missing 1 required positional argument: 'height'
I understand "Height" parameter is missing but how I compute this?.
