This question already has an answer here:
pandas groupby two columns and summarize by mean
(1 answer)
Closed 3 years ago.
I've the pandas dataframe like below
.
I want to transform this DataFrame into another form like below.
I've tried groupby functionality in pandas.But could not able to achieve the solution. Please help me with suggestions. Thanks inadvance.
e=df.groupby(['Country','City'])['Rating'].mean()
pd.DataFrame(e)
This would look like
Related
This question already has answers here:
How do I Pandas group-by to get sum?
(11 answers)
Closed last month.
Let's say I have the Python pandas dataframe below, I want to combine the amount paid column based on employee ID.
[dataframe]
Well try:
dataframe.groupby('EMPLOYEE_ID')['AMOUNT_PAID'].sum()
This question already has answers here:
How do I melt a pandas dataframe?
(3 answers)
Closed 6 months ago.
I have a table with 300 rows and 200 columns and i need to transform it.
I add an image of the transformation with an example table.
The table above is the original. The one below is the table after the transformation.
I was trying to solve it with excel and Pandas library of Python but i could not solve it.
Any ideas?
You can do a melt after reading excel using pandas:
df = pd.read_excel('your_excel_path')
df = pd.melt(df, id_vars='id', value_vars=['variable_1', 'variable_2'])
then write back to excel
df.to_excel('modified_excel.xlsx')
This question already has answers here:
How do I melt a pandas dataframe?
(3 answers)
Convert columns into rows with Pandas
(6 answers)
Closed last year.
In python and pandas I have a dataframe that I need to turn into tidy data to make charts easier
The original data is like this:
I want to transform into a dataframe, with the transposition of the data and adapting column names:
Please is there a way in python to do this?
Use melt:
out = df.melt('year', var_name='localization', value_name='number_of_tests')
You can also use:
out = df.set_index('year').rename_axis(columns='localization').unstack() \
.rename('number_of_tests').reset_index()
This question already has an answer here:
How is pandas groupby method actually working?
(1 answer)
Closed 3 years ago.
I want to use groupby function in pandas. However it doesn't work. Other function in pandas works very well. I'm very confused.
corr=corr.groupby(level='date')
print(corr)
Out[21]: <pandas.core.groupby.generic.DataFrameGroupBy object at 0x0000025FC4726808> ``
You need to apply an aggregation to it, for example
corr.groupby(level='date').sum()
This question already has answers here:
Filter pandas DataFrame by substring criteria
(17 answers)
Closed 7 years ago.
I have a DataFrame like this:
col1,col2
Sam,NL
Man,NL-USA
ho,CA-CN
And I would like to select the rows whose second column contains the word 'NL', which is something like SQL like command. Does anybody know about a similar command in Python Pandas?
The answer is here. Let df be your DataFrame.
df[df['col2'].str.contains('NL')]
This will select all the records that contain 'NL'.