pandas-melt

How can we melt a dataframe and list words under columns? Question: I have a dataframe that looks like this. import pandas as pd data = {‘clean_words’:[‘good’,’evening’,’how’,’are’,’you’,’how’,’can’,’i’,’help’], ‘start_time’:[1900,2100,2500,2750,2900,1500,1650,1770,1800], ‘end_time’:[2100,2500,2750,2900,3000,1650,1770,1800,1950], ‘transaction’:[1,1,1,1,1,2,2,2,2]} df = pd.DataFrame(data) df If I try a basic melt, like so… df_melted = df.pivot_table(index=’clean_words’, columns=’transaction’) df_melted.tail() I get this… What I really want is …

Turn the column names of a pandas df into a single column feature (with many nans) Question: pd.DataFrame({‘apple’: [np.nan, ‘Bad’, ‘Good’], ‘banana’: [np.nan, np.nan, np.nan], ‘orange’: [‘Good’, np.nan, np.nan]}) Right now, I have a pd dataframe in the format similar to below: apple banana orange 0 NaN NaN Good 1 Bad NaN NaN 2 Good …

melt() function duplicating dataset Question: I have a table like this: id name doggo floofer puppo pupper 1 rowa NaN NaN NaN NaN 2 ray NaN NaN NaN NaN 3 emma NaN NaN NaN pupper 4 sophy doggo NaN NaN NaN 5 jack NaN NaN NaN NaN 6 jimmy NaN NaN puppo NaN 7 bingo …

How do I melt a pandas dataframe? Question: On the pandas tag, I often see users asking questions about melting dataframes in pandas. I am going to attempt a canonical Q&A (self-answer) with this topic. I am is going to clarify: What is melt? How do I use melt? When do I use melt? I …