How plot multiple dictionaries of dataframes by columns ? Python Pandas

Question

I would like to plot multiple dictionaries of dataframes in the same figure with subplot. I can draw a dictionary of several dataframes on the same figure but I can't add another one.

keys = dfs.keys()

cols = 1
rows = 30

nb_figs = cols*rows

fig, ax = plt.subplots(nrows=rows, ncols=cols, figsize=(5, 150))

ax_array = ax.ravel()

# iterate through the dataframe dictionary keys and use enumerate
keys = sorted(dfs)
for idx, key in enumerate(keys[::150]):

    if idx >= nb_figs :
        break
    else:

        ax = dfs[key].plot(x='Timestamp', y='Value', ax= ax_array[idx])
        ax.xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y %H:%M:%S'))

fig.tight_layout()
plt.show()

• I would like to add a second column which would correspond to my second dataframes dictionary but do I have to make a for loop for the rows and columns to have a figure of dimension (36,2) ??
• How can I set the ax = ax_array or axto be in the right column and row?

The figure must be :

|-----------|   |-----------|
|           |   |           |
|    dict1  |   |    dict2  |
|    df1    |   |    df1    |
|-----------|   |-----------|

|-----------|         .
|           |         .
|    dict1  |         .
|    df2    |
|-----------|



|-----------|   |-----------|
|           |   |           |
|    dict1  |   |    dict2  |
|    df30   |   |    df30   |
|-----------|   |-----------|

```

Answer 1

When you create subplots with ncols>1 and nrows>1, you would get a two dimensional array of axis. So something like this:

cols = 2
rows = 30

nb_figs = cols*rows

fig, axes = plt.subplots(nrows=rows, ncols=cols, figsize=(5, 150))

for col, dfs in enumerate([dict1, dict2]):
    # use `.items()` to get pair of `key, value` so you don't need `dfs[key]`
    # or just `.values()` if you only need `data`
    for ax, (key, data) in zip(axes[:, col], dfs.items()):

        # plot data to ax
        data.plot(x='Timestamp', y='Value', ax=ax)
        ax.xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y %H:%M:%S'))


fig.tight_layout()
plt.show()