How to plot different groups of data from a dataframe into a single figure

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Try:

ax = df1.plot()
df2.plot(ax=ax)

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最佳答案

Chang's answer shows how to plot a different DataFrame on the same axes.
In this case, all of the data is in the same dataframe, so it's better to use groupby and unstack.
- Alternatively, pandas.DataFrame.pivot_table can be used.
- dfp = df.pivot_table(index='Month', columns='Year', values='value', aggfunc='mean')
When using pandas.read_csv, names= creates column headers when there are none in the file. The 'date' column must be parsed into datetime64[ns] Dtype so the .dt extractor can be used to extract the month and year.

import pandas as pd


# given the data in a file as shown in the op
df = pd.read_csv('temp.csv', names=['date', 'time', 'value'], parse_dates=['date'])
    

# create additional month and year columns for convenience
df['Year'] = df.date.dt.year
df['Month'] = df.date.dt.month


# groupby the month a year and aggreate mean on the value column
dfg = df.groupby(['Month', 'Year'])['value'].mean().unstack()


# display(dfg)
Year        2005  2006       2007  2012
Month
4            NaN  20.6        NaN  20.7
5            NaN   NaN  15.533333   NaN
8      19.566667   NaN        NaN   NaN

Now it's easy to plot each year as a separate line. The OP only has one observation for each year, so only a marker is displayed.

ax = dfg.plot(figsize=(9, 7), marker='.', xticks=dfg.index)

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If you a running Jupyter/Ipython notebook and having problems using;

ax = df1.plot()

df2.plot(ax=ax)

Run the command inside of the same cell!! It wont, for some reason, work when they are separated into sequential cells. For me at least.

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To do this for multiple dataframes, you can do a for loop over them:

fig = plt.figure(num=None, figsize=(10, 8))
ax = dict_of_dfs['FOO'].column.plot()
for BAR in dict_of_dfs.keys():
if BAR == 'FOO':
pass
else:
dict_of_dfs[BAR].column.plot(ax=ax)

This can also be implemented without the if condition:

fig, ax = plt.subplots()
for BAR in dict_of_dfs.keys():
dict_of_dfs[BAR].plot(ax=ax)

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You can make use of the hue parameter in seaborn. For example:

import seaborn as sns
df = sns.load_dataset('flights')


year month  passengers
0    1949   Jan         112
1    1949   Feb         118
2    1949   Mar         132
3    1949   Apr         129
4    1949   May         121
..    ...   ...         ...
139  1960   Aug         606
140  1960   Sep         508
141  1960   Oct         461
142  1960   Nov         390
143  1960   Dec         432


sns.lineplot(x='month', y='passengers', hue='year', data=df)