I try to create a histogram according to specified bins. Can not understand why the operation is taking up a very long time (almost more than 15 minutes) to execute? I went through the documentation of the functions involved but could not seem to find the reason behind it. I have an i3 5th Gen processor and 8 GB of RAM just in case this information is needed.
Here are details of the data involved
df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 50 entries, 0 to 49
Data columns (total 4 columns):
State 50 non-null object
Population 50 non-null int64
Murder.Rate 50 non-null float64
Abbreviation 50 non-null object
dtypes: float64(1), int64(1), object(2)
memory usage: 1.7+ KB
df.describe()
Population Murder.Rate
count 5.000000e+01 50.000000
mean 6.162876e+06 4.066000
std 6.848235e+06 1.915736
min 5.636260e+05 0.900000
25% 1.833004e+06 2.425000
50% 4.436370e+06 4.000000
75% 6.680312e+06 5.550000
max 3.725396e+07 10.300000
And the operation
df["Population"].hist(bins = np.arange(df["Population"].min(), df["Population"].max(), step=11))
