import matplotlib.pyplot as plt

from matplotlib.dates import date2num

import datetime

​

x = [

    datetime.datetime(2011, 1, 4, 0, 0),

    datetime.datetime(2011, 1, 5, 0, 0),

    datetime.datetime(2011, 1, 6, 0, 0)

]

x = date2num(x)

​

y = [4, 9, 2]

z = [1, 2, 3]

k = [11, 12, 13]

​

ax = plt.subplot(111)

ax.bar(x-0.2, y, width=0.2, color='b', align='center')

ax.bar(x, z, width=0.2, color='g', align='center')

ax.bar(x+0.2, k, width=0.2, color='r', align='center')

ax.xaxis_date()

​

plt.show()

ax = plt.subplot(111)

w = 0.3

ax.bar(x-w, y, width=w, color='b', align='center')

ax.bar(x, z, width=w, color='g', align='center')

ax.bar(x+w, k, width=w, color='r', align='center')

ax.xaxis_date()

ax.autoscale(tight=True)

​

plt.show()

​

import matplotlib.pyplot as plt

import datetime

​

x = [

    datetime.datetime(2011, 1, 4, 0, 0),

    datetime.datetime(2011, 1, 5, 0, 0),

    datetime.datetime(2011, 1, 6, 0, 0)

]

y = [4, 9, 2]

z = [1, 2, 3]

k = [11, 12, 13]

​

ax = plt.subplot(111)

ax.bar(x, y, width=0.5, color='b', align='center')

ax.bar(x, z, width=0.5, color='g', align='center')

ax.bar(x, k, width=0.5, color='r', align='center')

ax.xaxis_date()

​

plt.show()

fig, ax = plt.subplots()

data = {"Foo": [1, 2, 3, 4], "Zap": [0.1, 0.2], "Quack": [6], "Bar": [1.1, 2.2, 3.3, 4.4, 5.5]}

bar_plot(ax, data, group_stretch=0.8, bar_stretch=0.95, legend=True,

         labels=True, label_fontsize=8, barlabel_offset=0.05,

         bar_labeler=lambda k, i, s: str(round(s, 3)))

fig.show()

ax = plt.subplot(111)

w = 0.3

ax.bar(x-w, y, width=w, color='b', align='center')

ax.bar(x, z, width=w, color='g', align='center')

ax.bar(x+w, k, width=w, color='r', align='center')

ax.xaxis_date()

ax.autoscale(tight=True)

​

plt.show()

import pandas as pd

​

# using the existing lists from the OP, create the dataframe

df = pd.DataFrame(data={'y': y, 'z': z, 'k': k}, index=x)

​

# since there's no time component and x was a datetime dtype, set the index to be just the date

df.index = df.index.date

​

# display(df)

            y  z   k

2011-01-04  4  1  11

2011-01-05  9  2  12

2011-01-06  2  3  13

​

# plot bars or kind='barh' for horizontal bars; adjust figsize accordingly

ax = df.plot(kind='bar', rot=0, xlabel='Date', ylabel='Value', title='My Plot', figsize=(6, 4))

​

# add some labels

for c in ax.containers:

    # set the bar label

    ax.bar_label(c, fmt='%.0f', label_type='edge')

# add a little space at the top of the plot for the annotation

ax.margins(y=0.1)

​

# move the legend out of the plot

ax.legend(title='Columns', bbox_to_anchor=(1, 1.02), loc='upper left')

ax = df.plot(kind='barh', ylabel='Date', title='My Plot', figsize=(5, 4))

ax.set(xlabel='Value')

for c in ax.containers:

    # set the bar label

    ax.bar_label(c, fmt='%.0f', label_type='edge')

ax.margins(x=0.1)

​

# move the legend out of the plot

ax.legend(title='Columns', bbox_to_anchor=(1, 1.02), loc='upper left')

df = pd.DataFrame(zip(x*3, ["y"]*3+["z"]*3+["k"]*3, y+z+k), columns=["time", "kind", "data"])

plt.figure(figsize=(10, 6))

sns.barplot(x="time", hue="kind", y="data", data=df)

plt.show()

import numpy as np

import matplotlib.pyplot as plt

​

N = 3

ind = np.arange(N)  # the x locations for the groups

width = 0.27       # the width of the bars

​

fig = plt.figure()

ax = fig.add_subplot(111)

​

yvals = [4, 9, 2]

rects1 = ax.bar(ind, yvals, width, color='r')

zvals = [1,2,3]

rects2 = ax.bar(ind+width, zvals, width, color='g')

kvals = [11,12,13]

rects3 = ax.bar(ind+width*2, kvals, width, color='b')

​

ax.set_ylabel('Scores')

ax.set_xticks(ind+width)

ax.set_xticklabels( ('2011-Jan-4', '2011-Jan-5', '2011-Jan-6') )

ax.legend( (rects1[0], rects2[0], rects3[0]), ('y', 'z', 'k') )

​

def autolabel(rects):

    for rect in rects:

        h = rect.get_height()

        ax.text(rect.get_x()+rect.get_width()/2., 1.05*h, '%d'%int(h),

                ha='center', va='bottom')

​

autolabel(rects1)

autolabel(rects2)

autolabel(rects3)

​

plt.show()

def bar_plot(ax, data, group_stretch=0.8, bar_stretch=0.95,

             legend=True, x_labels=True, label_fontsize=8,

             colors=None, barlabel_offset=1,

             bar_labeler=lambda k, i, s: str(round(s, 3))):

    """

    Draws a bar plot with multiple bars per data point.

    :param dict data: The data we want to plot, wher keys are the names of each

      bar group, and items is a list of bar values for the corresponding group.

    :param float group_stretch: 1 means groups occupy the most (largest groups

      touch side to side if they have equal number of bars).

    :param float bar_stretch: If 1, bars within a group will touch side to side.

    :param bool x_labels: If true, x-axis will contain labels with the group

      names given at data, centered at the bar group.

    :param int label_fontsize: Font size for the label on top of each bar.

    :param float barlabel_offset: Distance, in y-values, between the top of the

      bar and its label.

    :param function bar_labeler: If not None, must be a functor with signature

      ``f(group_name, i, scalar)->str``, where each scalar is the entry found at

      data[group_name][i]. When given, returns a label to put on the top of each

      bar. Otherwise no labels on top of bars.

    """

    sorted_data = list(sorted(data.items(), key=lambda elt: elt[0]))

    sorted_k, sorted_v  = zip(*sorted_data)

    max_n_bars = max(len(v) for v in data.values())

    group_centers = np.cumsum([max_n_bars

                               for _ in sorted_data]) - (max_n_bars / 2)

    bar_offset = (1 - bar_stretch) / 2

    bars = defaultdict(list)

    #

    if colors is None:

        colors = {g_name: [f"C{i}" for _ in values]

                  for i, (g_name, values) in enumerate(data.items())}

    #

    for g_i, ((g_name, vals), g_center) in enumerate(zip(sorted_data,

                                                         group_centers)):

        n_bars = len(vals)

        group_beg = g_center - (n_bars / 2) + (bar_stretch / 2)

        for val_i, val in enumerate(vals):

            bar = ax.bar(group_beg + val_i + bar_offset,

                         height=val, width=bar_stretch,

                         color=colors[g_name][val_i])[0]

            bars[g_name].append(bar)

            if  bar_labeler is not None:

                x_pos = bar.get_x() + (bar.get_width() / 2.0)

                y_pos = val + barlabel_offset

                barlbl = bar_labeler(g_name, val_i, val)

                ax.text(x_pos, y_pos, barlbl, ha="center", va="bottom",

                        fontsize=label_fontsize)

    if legend:

        ax.legend([bars[k][0] for k in sorted_k], sorted_k)

    #

    ax.set_xticks(group_centers)

    if x_labels:

        ax.set_xticklabels(sorted_k)

    else:

        ax.set_xticklabels()

    return bars, group_centers