Notes on Pandas

Import and Export data

When importing and exporting Dataframe data, various formats are used, which are divided into

Refer to the IO Tools classification.

If you want to save as ASCII text, you can use To_csv to set parameters such as whether to save the index (line number).

Swap colums Order

If the original data is this:

In [6]: dfout[6]:          0         1         2         3         4      mean0  0.445598  0.173835  0.343415  0.682252  0.582616  0.4455431  0.881592  0.696942  0.702232  0.696724  0.373551  0.6702082  0.662527  0.955193  0.131016  0.609548  0.804694  0.6325963  0.260919  0.783467  0.593433  0.033426  0.512019  0.4366534  0.131842  0.799367  0.182828  0.683330  0.019485  0.3633715  0.498784  0.873495  0.383811  0.699289  0.480447  0.5871656  0.388771  0.395757  0.745237  0.628406  0.784473  0.5885297  0.147986  0.459451  0.310961  0.706435  0.100914  0.3451498  0.394947  0.863494  0.585030  0.565944  0.356561  0.5531959  0.689260  0.865243  0.136481  0.386582  0.730399  0.561593In [7]: cols = Df.columns.tolist () in [8]: colsout[8]: [0L, 1L, 2L, 3L, 4L, ' mean ']

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Change the order by swapping columns

In [a]: cols = cols[-1:] + cols[:-1] in []: colsout[]: ['mean', 0L, 1L, 2 L, 3L, 4L]

In turn, the following effects can be achieved

 in [+]: df = df[cols] #   in [ 17 17]: mean 0  1 2 3 40  0.445543 0 .445598 0.173835 0.343415 0.682252 0.5826161 0.670208 0.881592 0.696942 0.702232 0.696724 0.3735512 0.632596 0 .662527 0.955193 0.131016 0.609548 0.8046943 0.436653 0.260919 0.783467 0.593433 0.033426 0.5120194 0.363371 0 .131842 0.799367 0.182828 0.683330 0.0194855 0.587165 0.498784 0.873495 0.383811 0.699289 0.4804476 0.588529 0 .388771 0.395757 0.745237 0.628406 0.7844737 0.345149 0.147986 0.459451 0.310961 0.706435 0.1009148 0.553195 0 .394947 0.863494 0.585030 0.565944 0.3565619 0.561593 0.689260 0.865243 0.136481 0.386582 0.730399 

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(Reference source)

Notes on Pandas