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- value identifier
- 2007-01-01 0.781611 55
- 2007-01-01 0.766152 56
- 2007-01-01 0.766152 57
- 2007-02-01 0.705615 55
- 2007-02-01 0.032134 56
- 2007-02-01 0.032134 57
- 2008-01-01 0.026512 55
- 2008-01-01 0.993124 56
- 2008-01-01 0.993124 57
- 2008-02-01 0.226420 55
- 2008-02-01 0.033860 56
- 2008-02-01 0.033860 57
- df.groupby('identifier')
- df.groupby('identifier').plot(subplots=True)
- df.groupby('identifier').plot(subplots=False)
- plt.subplots(3,3)
- df.groupby('identifier').plot(subplots=True)
- import pandas as pd
- from numpy.random import randint
- import matplotlib.pyplot as plt
- df = pd.DataFrame(randint(0,10,(200,6)),columns=list('abcdef'))
- grouped = df.groupby('a')
- rowlength = grouped.ngroups/2 # fix up if odd number of groups
- fig, axs = plt.subplots(figsize=(9,4),
- nrows=2, ncols=rowlength, # fix as above
- gridspec_kw=dict(hspace=0.4)) # Much control of gridspec
- targets = zip(grouped.groups.keys(), axs.flatten())
- for i, (key, ax) in enumerate(targets):
- ax.plot(grouped.get_group(key))
- ax.set_title('a=%d'%key)
- ax.legend()
- plt.show()
- pd.pivot_table(df.reset_index(),
- index='index', columns='identifier', values='value'
- ).plot(subplots=True)
- pd.pivot_table(df.reset_index(),
- index='index', columns='identifier', values='value'
- )
- identifier 55 56 57
- index
- 2007-01-01 0.781611 0.766152 0.766152
- 2007-02-01 0.705615 0.032134 0.032134
- 2008-01-01 0.026512 0.993124 0.993124
- 2008-02-01 0.226420 0.033860 0.033860
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