In [65]: df
Out[65]:
one two
one 1 4
two 2 3
three 3 2
four 4 1
In [66]: df.drop(df.index[[1,3]])
Out[66]:
one two
one 1 4
three 3 2
Here is what the above code is Doing:
1. df.index returns the index of the dataframe
2. df.index[[1,3]] returns the index of the rows you want to drop
3. df.drop(df.index[[1,3]]) drops the rows with the index 1 and 3
def a(): val = True def b(): nonlocal val val = False Here is what the above code is Doing: 1. Defining a function a() 2. Defining a function b() inside a() 3. Declaring a nonlocal variable val inside b() 4. Assigning a value to val inside b() Now, let’s see what happens when we…
# Thank you AMLoucas from https://gist.github.com/betterdatascience/c455473d7445c0e7e279efe31a896e17 !! # Whoever is having the issue with ModuleNotFoundError: No module named ‘sklearn.neighbors.base’. this is because when importing missingpy it tries to import automatically ‘sklearn.neighbors.base’ however in the new versions of sklearn it has been renamed to ‘sklearn.neighbors._base’ so we have to manually import it to work. The code…
yourdf.drop([‘columnheading1’, ‘columnheading2′], axis=1, inplace=True) Here is what the above code is Doing: 1. We’re using the drop() method to drop the columns we don’t want. 2. We’re specifying the axis as 1, which means we’re dropping columns, not rows. 3. We’re setting the inplace parameter to True, which means we’re modifying the DataFrame in place.
days = [“Sunday”,”Monday”,”Tuesday”,”Wednesday”,”Thursday”,”Friday”,”Saturday”] for index,day in enumerate(days): #this will convert index starting from 0 to 1 if index >= 0: index += 1 print(index, day) Here is what the above code is Doing: 1. We create a list of days of the week. 2. We use the enumerate() function to get the index and value…
# install flask (basic, if path is not set yet) py -m pip install flask # or set PATH to use pip: setx PATH “%PATH%;C:\\Scripts” pip install flask # if “connection error: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed” [!]: py -m pip install –trusted-host pypi.python.org pip flask # if PermissionError: [WinError 5] Access is denied py…
# Plot frequency my_df[‘my_var’].value_counts().plot.bar() # Add column freq to the DF df[‘freq’]=df.groupby(by=’Name’)[‘Name’].transform(‘count’) Here is what the above code is Doing: 1. We use the .groupby() method to group the data by the Name column. 2. We use the .transform() method to apply the .count() method to the Name column. 3. We add the resulting series…