How can I plot separate Pandas DataFrames as subplots

Question

I have a few Pandas DataFrames sharing the same value scale  but having different columns and indices  When invoking df plot    I get separate plot images  what I really want is to have them all in the same plot as subplots  but I m unfortunately failing to come up with a solution to how and would highly appreciate some help

User · Accepted Answer

You can manually create the subplots with matplotlib, and then plot the dataframes on a specific subplot using the ax keyword. For example for 4 subplots (2x2):

import matplotlib.pyplot as plt

fig, axes = plt.subplots(nrows=2, ncols=2)

df1.plot(ax=axes[0,0])
df2.plot(ax=axes[0,1])
...

Here axes is an array which holds the different subplot axes, and you can access one just by indexing axes.
If you want a shared x-axis, then you can provide sharex=True to plt.subplots.

User · Answer

You can use this   fig   plt figure   ax   fig add subplot 221  plt plot x y   ax   fig add subplot 222  plt plot x z       plt show

User · Answer

How to create multiple plots from a dictionary of dataframes with long  tidy  data  Assumptions  There is a dictionary of multiple dataframes of tidy data  Created by reading in from files Created by separating a single dataframe into multiple dataframes   The categories  cat  may be overlapping  but all dataframes may not contain all values of cat hue  cat    Because dataframes are being iterated through  there s not guarantee that colors will be mapped the same for each plot  A custom color map needs to be created from the unique  cat  values for all the dataframes Since the colors will be the same  place one legend to the side of the plots  instead of a legend in every plot    Imports and synthetic data import pandas as pd import numpy as np    used for random data import random    used for random data import matplotlib pyplot as plt from matplotlib patches import Patch    for custom legend import seaborn as sns import math import ceil    determine correct number of subplot     synthetic data df dict   dict   for i in range 1  7       np random seed i      random seed i      data length   100     data     cat    random choice   A    B    C    for   in range data length                 x   np random rand data length                y   np random rand data length       df dict i    pd DataFrame data      display df dict 1  head       cat         x         y 0   A  0 417022  0 326645 1   C  0 720324  0 527058 2   A  0 000114  0 885942 3   B  0 302333  0 357270 4   A  0 146756  0 908535  Create color mappings and plot   create color mapping based on all unique values of cat unique cat    cat for v in df dict values   for cat in v cat unique       get unique cats colors   sns color palette  husl   n colors len unique cat      get a number of colors cmap   dict zip unique cat  colors      zip values to colors    iterate through dictionary and plot col nums   3    how many plots per row row nums   math ceil len df dict    col nums     how many rows of plots plt figure figsize  10  5      change the figure size as needed for i   k  v  in enumerate df dict items    1       plt subplot row nums  col nums  i     create subplots     p   sns scatterplot data v  x  x   y  y   hue  cat   palette cmap      p legend  remove      remove the individual plot legends     plt title f DataFrame   k     plt tight layout     create legend from cmap patches    Patch color v  label k  for k  v in cmap items      place legend outside of plot  change the right bbox value to move the legend up or down plt legend handles patches  bbox to anchor  1 06  1 2   loc  center left   borderaxespad 0  plt show

User · Answer

You may not need to use Pandas at all  Here s a matplotlib plot of cat frequencies     x   np linspace 0  2 np pi  400  y   np sin x  2   f  axes   plt subplots 2  1  for c  i in enumerate axes     axes c  plot x  y    axes c  set title  cats   plt tight layout

User · Answer

Here is a working pandas subplot example  where modes is the column names of the dataframe      dpi 200     figure size  20  10      fig  ax   plt subplots len modes   1  sharex  quot all quot   sharey  quot all quot   dpi dpi      for i in range len modes            ax i    pivot df loc    modes i   plot bar figsize  figure size 0   figure size 1  len modes                                                       ax ax i   title modes i   color my colors i           ax i  legend       fig suptitle name

User · Answer

You can plot multiple subplots of multiple pandas data frames using matplotlib with a simple trick of making a list of all data frame  Then using the for loop for plotting subplots    Working code    import matplotlib pyplot as plt import pandas as pd import numpy as np   dataframe sample data df1   pd DataFrame np random rand 10 2  100  columns   A    B    df2   pd DataFrame np random rand 10 2  100  columns   A    B    df3   pd DataFrame np random rand 10 2  100  columns   A    B    df4   pd DataFrame np random rand 10 2  100  columns   A    B    df5   pd DataFrame np random rand 10 2  100  columns   A    B    df6   pd DataFrame np random rand 10 2  100  columns   A    B     define number of rows and columns for subplots nrow 3 ncol 2   make a list of all dataframes  df list    df1  df2  df3  df4  df5  df6  fig  axes   plt subplots nrow  ncol    plot counter count 0 for r in range nrow       for c in range ncol           df list count  plot ax axes r c           count  1     Using this code you can plot subplots in any configuration  You need to just define number of rows nrow and number of columns ncol  Also  you need to make list of data frames df list which you wanted to plot

User · Answer

Building on  joris response above  if you have already established a reference to the subplot  you can use the reference as well  For example    ax1   plt subplot2grid  50 100    0  0   colspan 20  rowspan 10       df plot barh ax ax1  stacked True

User · Answer

You can use the familiar Matplotlib style calling a figure and subplot  but you simply need to specify the current axis using plt gca    An example   plt figure 1  plt subplot 2 2 1  df A plot    no need to specify for first axis plt subplot 2 2 2  df B plot ax plt gca    plt subplot 2 2 3  df C plot ax plt gca      etc

User · Answer

You can see e gs  in the documentation demonstrating joris answer  Also from the documentation  you could also set subplots True and layout     within the pandas plot function     df plot subplots True  layout  1 2     You could also use fig add subplot   which takes subplot grid parameters such as 221  222  223  224  etc  as described in the post here  Nice examples of plot on pandas data frame  including subplots  can be seen in this ipython notebook

[python] How can I plot separate Pandas DataFrames as subplots?

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