WebDec 23, 2024 · Method 1: Using the rev method. The rev () method in R is used to return the reversed order of the R object, be it dataframe or a vector. It computes the reverse columns by default. The resultant dataframe returns the last column first followed by the previous columns. The ordering of the rows remains unmodified. WebAlso, within data.table::transpose you can use the arguments make.names to select the column (usually a character vector) whose names will become the column names for the transposed data.frame. You can also use the argument keep.names to choose a column name for the new column (a character vector) which will store the previous column …
python - Flip a Dataframe - Stack Overflow
WebJun 21, 2024 · I have below dataframe and want to transpose the columns aftr 3rd column into rows. Please help on this. df: country year perc data1 data2 data3 IN 2015 hjk 75 81 96 US 2015 KTM 100 289 632 Results: country year perc TransposedColumn Value IN 2015 hjk data1 75 IN 2015 hjk data2 81 IN 2015 hjk data3 96 US 2015 KTM data1 100 US … WebNov 1, 2024 · pd.wide_to_long. You can add a prefix to your year columns and then feed directly to pd.wide_to_long.I won't pretend this is efficient, but it may in certain situations be more convenient than pd.melt, e.g. when your columns already have an appropriate prefix.. df.columns = np.hstack((df.columns[:2], df.columns[2:].map(lambda x: f'Value{x}'))) res … smart board business applications
r - Transposing in dplyr - Stack Overflow
WebIn the case of two values, it appears that you only want the first (e.g. the last row of your example). You can use loc to first set the second value to None in the case both columns have values.. df.loc[(df.Col1.notnull()) & (df.Col2.notnull()), 'Col2'] = None WebDec 1, 2015 · 5 Answers. library (tidyr) library (dplyr) df %>% mutate (group = 1) %>% spread (HEADER, price) group AWAY_TEAM AWAY_TRPM HOME_TEAM HOME_TRPM 1 1 NOP -0.845186446996287 CHA 0.863104076023855. Using this, you can specify your groupings - and you can add on select (-group) to remove them later. Future users … WebApr 17, 2024 · 28. You need set_index with transpose by T: print (df.set_index ('fruits').T) fruits apples grapes figs numFruits 10 20 15. If need rename columns, it is a bit complicated: print (df.rename (columns= {'numFruits':'Market 1 Order'}) .set_index ('fruits') .rename_axis (None).T) apples grapes figs Market 1 Order 10 20 15. hill of grace 1991