python - pandas - select/mask the first n elements by value -


starting 1 single dataframe:

i,a,b,c,d,e,f a,1,3,5,6,4,2 b,3,4,7,1,0,0 c,1,3,5,2,0,7

i keep/mask first 3 elements in rows value keeping order of columns, resulting dataframe appears as:

i,a,b,c,d,e,f a,0,0,5,6,4,0 b,3,4,7,0,0,0 c,0,3,5,0,0,7

so far i've been able sort dataframe with:

a = df.values

and

a.sort(axis=1)

so that:

[[1 1 2 3 4 5]  [0 0 1 1 3 4]  [0 1 1 3 5 7]]

obtaining sorted numpy array, loosing information columns.

you can rank values row-wise , filter them , call fillna:

in [248]: df[df.rank(axis=1, method='min')>3].fillna(0)  out[248]:      b  c  d  e  f 0  0  0  0  5  6  4  0 1  0  3  4  7  0  0  0 2  0  0  3  5  0  0  7

you can concat 'i' column back:

in [268]: pd.concat([df['i'], df[df.rank(axis=1, method='min')>3].fillna(0)[df.columns[1:]]], axis=1)  out[268]:      b  c  d  e  f 0   0  0  5  6  4  0 1  b  3  4  7  0  0  0 2  c  0  3  5  0  0  7

output intermediate dfs:

in [269]:  df.rank(axis=1, method='min') out[269]:     b  c  d  e  f 0  1  3  5  6  4  2 1  4  5  6  3  1  1 2  2  4  5  3  1  6 in [270]:  df.rank(axis=1, method='min')>3 out[270]:             b     c      d      e      f 0  false  false  true   true   true  false 1   true   true  true  false  false  false 2  false   true  true  false  false   true

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