I have this dataset: Account lookup FY11USD FY12USD FY11local FY12local Sales CA 1000 5000 800 4800 Sales JP 5000 6500 10 15 Trying to arrive to get the data
I have a table like this device_type version pool testMean testP50 testP90 testP99 testStd WidgetMean WidgetP50 WidgetP90 WidgetP99 WidgetStd PNB0Q
I have a table like this device_type version pool testMean testP50 testP90 testP99 testStd WidgetMean WidgetP50 WidgetP90 WidgetP99 WidgetStd PNB0Q
Is it possible to end up with a categorical variable column after a melt operation in pandas? If I set up the data like this: import pandas as pd import numpy a
How can I melt a pandas data frame using multiple variable names and values? I have the following data frame that changes its shape in a for loop. In one of the
I would like to melt several groups of columns of a dataframe into multiple target columns. Similar to questions Python Pandas Melt Groups of Initial Columns In
wondering if pd.melt supports melting multiple columns. I have the below examples trying to have the value_vars as list of lists but i am getting an error: Val