Matplotlib轴仅在Dataframe上具有值

Question

从去年开始，我一直在做积压工作表，现在是新年，现在我面临着这个问题：

我必须乘以一年中的数字，以保持X轴一直向右滚动。 但在那之后，我在X轴上得到了从202052年到202099年的这个空白区间

我的索引没有这些值。详情如下:

(Int64Index([202026, 202027, 202028, 202029, 202030, 202031, 202032, 202033,
             202035, 202036, 202037, 202038, 202040, 202041, 202043, 202044,
             202045, 202046, 202047, 202048, 202049, 202050, 202051, 202052,
             202101, 202102],
            dtype='int64'),
 Int64Index([202026, 202027, 202028, 202029, 202030, 202031, 202032, 202033,
             202034, 202035, 202036, 202037, 202038, 202040, 202041, 202043,
             202044, 202045, 202046, 202047, 202048, 202049, 202050, 202051,
             202052, 202101, 202102],
            dtype='int64'),
 Int64Index([202026, 202027, 202028, 202029, 202030, 202031, 202032, 202033,
             202034, 202035, 202036, 202037, 202038, 202040, 202041, 202043,
             202044, 202045, 202046, 202047, 202048, 202049, 202050, 202051,
             202052, 202101, 202102],
            dtype='int64'))

如何删除这些值

谢谢大家!

编辑：添加完整代码

import matplotlib.pyplot as plt
import pandas as pd
from datetime import datetime, timedelta
from matplotlib.lines import Line2D
import matplotlib.dates as mdates
import matplotlib.cbook as cbook
from matplotlib.ticker import MaxNLocator

%matplotlib inline

df = pd.read_csv(
    "/home/eklon/Downloads/Venturus/NetSuite/Acompanhamento/130121/MelhoriasNetSuite130121.csv", delimiter=';')


df.columns = df.columns.str.replace(' ', '')    

df['CreatedDate'] = pd.to_datetime(df['CreatedDate'])
df['CompletedDate'] = pd.to_datetime(df['CompletedDate'])
df['DayCompleted'] = df['CompletedDate'].dt.dayofweek
df['DayCreated'] = df['CreatedDate'].dt.dayofweek
df['WeekCreated'] = df['CreatedDate'].dt.isocalendar().week
df['WeekCompleted'] = df['CompletedDate'].dt.isocalendar().week
df['YearCreated'] = df['CreatedDate'].dt.year
df['YearCompleted'] = df['CompletedDate'].dt.year
df['firstCompletedDate'] = df.CompletedDate - df.DayCompleted * timedelta(days=1)
df['firstCreatedDate'] = df.CreatedDate - df.DayCreated * timedelta(days=1)

df['YearWeekCreated'] = df['YearCreated']*100 + df['WeekCreated']
df['YearWeekCompleted'] = df['YearCompleted']*100 + df['WeekCompleted']


df_done = df[df['Progress'] == 'Completed']
df_open = df[df['Progress'] != 'Completed']
df_todo = df[df['BucketName'] == 'To do']
df_doing = df[df['BucketName'] == 'Doing']
df_consult = df[df['BucketName'] == 'Em andamento RSM']
df_open['Priority'].value_counts().sort_index()
df['Priority'].sort_index()

df_backlog_created = df['YearWeekCreated'].value_counts().sort_index()
df_backlog_completed = df['YearWeekCompleted'].value_counts().sort_index()
df_backlog = df_backlog_created.cumsum() - df_backlog_completed.cumsum()




#============================================================================


qtd_created = df['YearWeekCreated'].value_counts().sort_index()
idx_created = qtd_created.index
qtd_completed = df['YearWeekCompleted'].value_counts().sort_index()
idx_completed = qtd_completed.index 
qtd_backlog = df_backlog
idx_backlog = qtd_backlog.index

idx_completed = idx_completed.astype(int)


fig, ax = plt.subplots(figsize=(14,10))



#plt.figure(figsize=(14,10))
ax.plot(idx_created, list(qtd_created), label="Iniciadas", color="r")
ax.plot(idx_completed, list(qtd_completed), label="Completadas", color="y", linewidth=3)
ax.bar(idx_backlog, qtd_backlog, label="Backlog", color="b")
ax.legend(['Novas', 'Fechadas', 'Backlog'])



x=[1,2,3]
y=[9,8,7]


for a,b in zip(idx_created, qtd_created): 
    plt.text(a, b, str(b), fontsize=12, color='w', bbox=dict(facecolor='red', alpha=0.5), horizontalalignment='center')




for a,b in zip(idx_backlog, qtd_backlog): 
    plt.text(a, b, str(b), fontsize=12, color='w', bbox=dict(facecolor='blue', alpha=0.5), horizontalalignment='center')



for a,b in zip(idx_completed, qtd_completed): 
    plt.text(a, b, str(b), fontsize=12, color='black', bbox=dict(facecolor='yellow', alpha=0.5))


plt.title('Backlog', fontsize= 20)

Answer 1

这不是对代码的直接修复，但原则应该是相同的。 我将创建一个假数据帧，并说明问题和解决方案

当前的空空间问题：

labels = [202026, 202027, 202028, 202029, 202030, 202031, 202032, 202033,
             202034, 202035, 202036, 202037, 202038, 202040, 202041, 202043,
             202044, 202045, 202046, 202047, 202048, 202049, 202050, 202051,
             202052, 202101, 202102]
y = np.random.rand(len(labels))

# old approach, will have empty space
_, ax = plt.subplots(1,1)
ax.plot(labels, y)

建议的解决办法：

labels = [202026, 202027, 202028, 202029, 202030, 202031, 202032, 202033,
             202034, 202035, 202036, 202037, 202038, 202040, 202041, 202043,
             202044, 202045, 202046, 202047, 202048, 202049, 202050, 202051,
             202052, 202101, 202102]
y = np.random.rand(len(labels))

# suggested by dummy index
x_idx = range(len(labels))
_, ax = plt.subplots(1,1)
ax.plot(x_idx, y)
ax.set_xticks(x_idx[::5])
ax.set_xticklabels(labels[::5])

希望这对你有用。韩元

Answer 2

您要做的是称为索引绘制（只需将y值传递给plot，没有x值），因此应该使用^{}。在以下示例中，每第4行设置一个勾号：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mt

np.random.seed(0)
idx = [202026, 202027, 202028, 202029, 202030, 202031, 202032, 202033,
             202035, 202036, 202037, 202038, 202040, 202041, 202043, 202044,
             202045, 202046, 202047, 202048, 202049, 202050, 202051, 202052,
             202101, 202102]
df = pd.DataFrame(np.random.rand(len(idx)), index=idx, columns=['col1'])

fig,ax = plt.subplots()
ax.plot(df.col1.to_numpy())
ax.xaxis.set_major_locator(mt.IndexLocator(4,0))
ax.xaxis.set_ticklabels(df.iloc[ax.get_xticks()].index)

另一种可能是使用^{}，特别是如果您想缩放图表，因为它将动态格式化自动跟踪标记：

ax.xaxis.set_major_formatter(mt.FuncFormatter(lambda x,_: f'{df.index[int(x)]}' if x in range(len(df)) else ''))