没有 NaN 值空间的 Pandas 绘图条

Question

我有一个包含 NaN 值的 Pandas DataFrame。我想用 x 轴中的索引制作一个条形图，每列都有一个条形图，按索引分组。我只想绘制具有实际值的条形图。

就我尝试而言，从这个例子中：

df = pandas.DataFrame({'foo':[1,None,None], 'bar':[None,2,0.5], 'col': [1,1.5,None]}, index=["A","B","C"])
df.plot.bar()
plt.show()

我可以制作这个情节：

我想要的是删除 NaN 列留下的空格。因此，要压缩条形并将组居中在 x 刻度上方。

Answer 1

您可以执行类似下面代码的操作，方法是遍历数据帧的每一行并检查每一列是否有 NaN。

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(
    {"foo": [1, None, None], "bar": [None, 2, 0.5], "col": [1, 1.5, None]},
    index=["A", "B", "C"],
)


# define the colors for each column
colors = {"foo": "blue", "bar": "orange", "col": "green"}

fig = plt.figure(figsize=(10, 6))
ax = plt.gca()

# width of bars
width = 1

# create emptly lists for x tick positions and names
x_ticks, x_ticks_pos = [], []

# counter for helping with x tick positions
count = 0

# reset the index
# so that we can iterate through the numbers.
# this will help us to get the x tick positions
df = df.reset_index()
# go through each row of the dataframe
for idx, row in df.iterrows():
    # this will be the first bar position for this row
    count += idx

    # this will be the start of the first bar for this row
    start_idx = count - width / 2
    # this will be the end of the last bar for this row
    end_idx = start_idx
    # for each column in the wanted columns,
    # if the row is not null,
    # add the bar to the plot
    # also update the end position of the bars for this row
    for column in df.drop(["index"], axis=1).columns:
        if row[column] == row[column]:
            plt.bar(count, row[column], color=colors[column], width=width, label=column)
            count += 1
            end_idx += width
    # this checks if the row had any not NULL value in the desired columns
    # in other words, it checks if there was any bar for this row
    # if yes, add the center of all the row's bars and the row's name (A,B,C) to the respective lists
    if end_idx != start_idx:
        x_ticks_pos.append((end_idx + start_idx) / 2)
        x_ticks.append(row["index"])

# now set the x_ticks
plt.xticks(x_ticks_pos, x_ticks)

# also plot the legends
# and make sure to not display duplicate labels
# the below code is taken from:
# /sf/ask/951224431/
handles, labels = plt.gca().get_legend_handles_labels()
by_label = dict(zip(labels, handles))
plt.legend(by_label.values(), by_label.keys())
plt.show()

结果：