python - Pandas data frame with repeating sequences: How to do a spaghetti plot? -

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i've got data looking following data pandas.dataframe:

                                  diff_1       diff_2 1949-01-01 06:00:00               -0.555       -0.123 1949-01-01 07:00:00               -0.654        0.230 1949-01-02 06:00:00               -0.879        0.012 1949-01-02 07:00:00               -0.459        0.672 1949-01-03 06:00:00               -0.588        0.980 1949-01-03 07:00:00               -0.068        0.375 1950-01-01 06:00:00               -0.654        0.572 1950-01-01 07:00:00               -0.544        0.092 1950-01-02 06:00:00                0.374       -0.275 1950-01-02 07:00:00                0.562       -0.260 1950-01-03 06:00:00               -0.200        0.240 1950-01-03 07:00:00               -0.226        0.202

now, want "spaghetti plot", "spaghetti groups" in 1 color determinated whether curve diff_1 or diff_2 (so x-axis time 01-01 01-03, y-axis differences, each "spaghetti" 1 year). tried orient @ question:

plot pandas data frame year on year data

however, fear have got 1 dimension many. ideas how work?

edit: following simple image illustrates i'm looking for. multiple lines 1 color result fact time period on x-axis repeat annually.

enter image description here

this best do, not totally satisfied might enough:

# add column year can pivot on later. tdf = df.assign(year=df.index.year) # make dates have same year (a leap 1 in case) tdf.index = df.index.map(lambda x: x.replace(year=2004)) # pivot using years columns , put them in topmost level. tdf = (tdf.pivot(columns='year').swaplevel(0, 1, axis='columns')) print(tdf)  year                  1949   1950   1949   1950                     diff_1 diff_1 diff_2 diff_2 2004-01-01 06:00:00 -0.555 -0.654 -0.123  0.572 2004-01-01 07:00:00 -0.654 -0.544  0.230  0.092 2004-01-02 06:00:00 -0.879  0.374  0.012 -0.275 2004-01-02 07:00:00 -0.459  0.562  0.672 -0.260 2004-01-03 06:00:00 -0.588 -0.200  0.980  0.240 2004-01-03 07:00:00 -0.068 -0.226  0.375  0.202  # create list of many colors columns in df color = [c['color'] c in plt.rcparams['axes.prop_cycle'][:df.columns.size]] # plot ax = plt.subplot() year in tdf.columns.levels[0]:     tdf[year].plot(color=color, legend=false, ax=ax) plt.legend(ax.lines[:df.columns.size], df.columns, loc='best') plt.show()

enter image description here

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