如何用 pandas 数据框中的列(从第3列值)来标记折线图? [英] How to label line chart with column from pandas dataframe (from 3rd column values)?

问题描述

我有一个数据集已过滤为以下内容(样本数据):

Name Time l
1 1.129 1G-d
1 0.113 1G-a
1 3.374 1B-b
1 3.367 1B-c
1 3.374 1B-d
2 3.355 1B-e
2 3.361 1B-a
3 1.129 1G-a

在过滤数据框并将其转换为CSV文件后，我得到了以下数据:

 # Assigns the new data frame to "df" with the data from only three columns
header = ['Names','Time','l']
df = pd.DataFrame(df_2, columns = header)

# Sorts the data frame by column "Names" as integers
df.Names = df.Names.astype(int)
df = df.sort_values(by=['Names'])

# Changes the data to match format after converting it to int
df.Time=df.Time.astype(int)
df.Time = df.Time/1000

csv_file = df.to_csv(index=False, columns=header, sep=" " )
 

现在，我正在尝试用标记为每个标签列数据/项目绘制线条. 我希望将列l作为我的行名(标签)-每个列都作为新行，将Time作为我的Y轴值，将Names作为我的X轴值. 因此，在这种情况下，图形中将有7条带有以下标签的不同线:1G-d, 1G-a, 1B-b, 1B-c, 1B-d, 1B-e, 1B-a.

到目前为止，我已经完成了以下附加设置，但是我不确定如何绘制线条.

 plt.xlim(0, 60)
plt.ylim(0, 18)
plt.legend(loc='best')
plt.show()
 

我使用了sns.lineplot，它带有色相，并且我不想为标签框命名.另外，在那种情况下，如果不添加样式的新列就无法拥有标记.

我也尝试了ply.plot，但是在那种情况下，我不确定如何增加行数.我只能给出只能创建一行的x和y值.

如果还有其他来源，请在下面告诉我.

谢谢

我想要的最终图形如下所示，但带有标记:

解决方案

您可以对seaborn的lineplot进行一些调整.由于您的样本还不够长，无法使用它来演示:

 # Create data
np.random.seed(2019)
categories = ['1G-d', '1G-a', '1B-b', '1B-c', '1B-d', '1B-e', '1B-a']
df = pd.DataFrame({'Name':np.repeat(range(1,11), 10),
              'Time':np.random.randn(100).cumsum(),
              'l':np.random.choice(categories, 100)
        })

# Plot
sns.lineplot(data=df, x='Name', y='Time', hue='l', style='l', dashes=False,
             markers=True, ci=None, err_style=None)

# Temporarily removing limits based on sample data
#plt.xlim(0, 60)
#plt.ylim(0, 18)

# Remove seaborn legend title & set new title (if desired)
ax = plt.gca()
handles, labels = ax.get_legend_handles_labels()
ax.legend(handles=handles[1:], labels=labels[1:], title='New Title', loc='best')

plt.show()
 

• 要应用标记，必须指定一个style变量.这可以与hue相同.
• 您可能要删除dashes，ci和err_style
• 要删除原始的图例标题，可以获取handles和labels，然后重新添加图例而无需第一个手柄和标签.您还可以在此处指定位置，并根据需要设置新标题(或仅删除title=...而不显示标题).

---

每个评论的编辑次数:

可以很容易地通过以下方法将数据过滤到仅一个级别类别的子集中:

 categories = ['1G-d', '1G-a', '1B-b', '1B-c', '1B-d', '1B-e', '1B-a']
df = df.loc[df['l'].isin(categories)]
 

如果级别太多，

markers=True将失败.如果您只对出于美学目的标记点感兴趣，只需将单个标记乘以您感兴趣的类别数即可(markers='o'*len(categories).您已经创建了该标记，可以将数据过滤到感兴趣的类别).. >

或者，您可以指定自定义词典以传递给markers参数:

 points = ['o', '*', 'v', '^']
mult = len(categories) // len(points) + (len(categories) % len(points) > 0)
markers = {key:value for (key, value) 
           in zip(categories, points * mult)}
 

这将返回类别-点组合的字典，在指定的标记点上循环，直到categories中的每个项目都具有点样式.

I have a data set I filtered to the following (sample data):

Name Time l
1 1.129 1G-d
1 0.113 1G-a
1 3.374 1B-b
1 3.367 1B-c
1 3.374 1B-d
2 3.355 1B-e
2 3.361 1B-a
3 1.129 1G-a

I got this data after filtering the data frame and converting it to CSV file:

# Assigns the new data frame to "df" with the data from only three columns
header = ['Names','Time','l']
df = pd.DataFrame(df_2, columns = header)

# Sorts the data frame by column "Names" as integers
df.Names = df.Names.astype(int)
df = df.sort_values(by=['Names'])

# Changes the data to match format after converting it to int
df.Time=df.Time.astype(int)
df.Time = df.Time/1000

csv_file = df.to_csv(index=False, columns=header, sep=" " )

Now, I am trying to graph lines for each label column data/items with markers. I want the column l as my line names (labels) - each as a new line, Time as my Y-axis values and Names as my X-axis values. So, in this case, I would have 7 different lines in the graph with these labels: 1G-d, 1G-a, 1B-b, 1B-c, 1B-d, 1B-e, 1B-a.

I have done the following so far which is the additional settings, but I am not sure how to graph the lines.

plt.xlim(0, 60)
plt.ylim(0, 18)
plt.legend(loc='best')
plt.show()

I used sns.lineplot which comes with hue and I do not want to have name for the label box. Also, in that case, I cannot have the markers without adding new column for style.

I also tried ply.plot but in that case, I am not sure how to have more lines. I can only give x and y values which create only one line.

If there's any other source, please let me know below.

Thanks

The final graph I want to have is like the following but with markers:

解决方案

You can apply a few tweaks to seaborn's lineplot. Using some created data since your sample isn't really long enough to demonstrate:

# Create data
np.random.seed(2019)
categories = ['1G-d', '1G-a', '1B-b', '1B-c', '1B-d', '1B-e', '1B-a']
df = pd.DataFrame({'Name':np.repeat(range(1,11), 10),
              'Time':np.random.randn(100).cumsum(),
              'l':np.random.choice(categories, 100)
        })

# Plot
sns.lineplot(data=df, x='Name', y='Time', hue='l', style='l', dashes=False,
             markers=True, ci=None, err_style=None)

# Temporarily removing limits based on sample data
#plt.xlim(0, 60)
#plt.ylim(0, 18)

# Remove seaborn legend title & set new title (if desired)
ax = plt.gca()
handles, labels = ax.get_legend_handles_labels()
ax.legend(handles=handles[1:], labels=labels[1:], title='New Title', loc='best')

plt.show()

• To apply markers, you have to specify a style variable. This can be the same as hue.
• You likely want to remove dashes, ci, and err_style
• To remove the seaborn legend title, you can get the handles and labels, then re-add the legend without the first handle and label. You can also specify the location here and set a new title if desired (or just remove title=... for no title).

---

Edits per comments:

Filtering your data to only a subset of level categories can be done fairly easily via:

categories = ['1G-d', '1G-a', '1B-b', '1B-c', '1B-d', '1B-e', '1B-a']
df = df.loc[df['l'].isin(categories)]

markers=True will fail if there are too many levels. If you are only interested in marking points for aesthetic purposes, you can simply multiply a single marker by the number of categories you are interested in (which you have already created to filter your data to categories of interest): markers='o'*len(categories).

Alternatively, you can specify a custom dictionary to pass to the markers argument:

points = ['o', '*', 'v', '^']
mult = len(categories) // len(points) + (len(categories) % len(points) > 0)
markers = {key:value for (key, value) 
           in zip(categories, points * mult)}

This will return a dictionary of category-point combinations, cycling over the marker points specified until each item in categories has a point style.

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