[英]How to correct overlapping tick labels in matplotlib plot?
I have the dataframes ready to plot, but when I use matplotlib to plot these data the lines are not correct and do not show the trend.我已经准备好绘制数据框,但是当我使用 matplotlib 绘制这些数据时,线条不正确并且没有显示趋势。
for example, the first graph should be a curly line, however, I got a straight line plotted in the graph.例如,第一个图形应该是一条卷线,但是,我在图形中绘制了一条直线。
I wonder how to plot these lines correctly?我想知道如何正确绘制这些线? and fix both axis?并修复两个轴?
import pandas as pd
import datetime as dt
import pandas_datareader as web
import matplotlib.pyplot as plt
from matplotlib import style
import matplotlib.ticker as ticker
from bs4 import BeautifulSoup
import requests
import matplotlib.dates as mdates
url = 'https://www.federalreserve.gov/data.xml'
soup = BeautifulSoup(requests.get(url).content, 'html.parser')
for chart in soup.select('chart'):
series = {}
index = []
for s in chart.select('series'):
series[s['description']] = []
temp_index = []
for o in s.select('observation'):
temp_index.append(o['index'])
series[s['description']].append(o['value'])
if len(temp_index) > len(index):
index = temp_index
series['index'] = index
max_len = len(max(series.values(), key=len))
for k in series:
series[k] = series[k] + ['No Data'] * (max_len - len(series[k]))
df = pd.DataFrame(series).set_index('index')
print(df)
print('-' * 80)
plt.figure()
for i in df:
plt.plot(df.index,df[i],label=chart['title'])
plt.show()
df.index = pd.to_datetime(df.index)
has been added df.index = pd.to_datetime(df.index)
已添加df = pd.DataFrame(series, dtype=float).set_index('index')
will catch most of the columns, but there are some columns that still have stings, so can't be converted df = pd.DataFrame(series, dtype=float).set_index('index')
会捕获大部分的列,但是有一些列仍然有刺,所以无法转换print(df.info())
has been added. print(df.info())
已添加。 Review and fix any column that is an object
.查看并修复作为object
任何列。 That means the column contains some strings and can't be converted to a float.这意味着该列包含一些字符串并且无法转换为浮点数。
[np.nan]
instead of ['No Data']
, so the column can be set as a float, which will allow it to plot correctly.使用[np.nan]
而不是['No Data']
,因此可以将列设置为浮点数,这将使其能够正确绘图。import numpy as np
url = 'https://www.federalreserve.gov/data.xml'
soup = BeautifulSoup(requests.get(url).content, 'html.parser')
for chart in soup.select('chart'):
series = {}
index = []
for s in chart.select('series'):
series[s['description']] = []
temp_index = []
for o in s.select('observation'):
temp_index.append(o['index'])
series[s['description']].append(o['value'])
if len(temp_index) > len(index):
index = temp_index
series['index'] = index
max_len = len(max(series.values(), key=len))
for k in series:
# adding No Data is preventing the the column from being interpreted as a float
series[k] = series[k] + [np.nan] * (max_len - len(series[k]))
df = pd.DataFrame(series, dtype=float).set_index('index') # added dtype=float
df.index = pd.to_datetime(df.index) # convert the index to a datetime format
print(df)
print(df.info()) # review the printed info, any column that isn't a float has strings in it the must be fixed
print('-' * 80)
plt.figure()
for i in df:
plt.figure(figsize=(9, 5))
plt.plot(df.index, df[i])
plt.title(f'{chart["title"]}\n{i}')
plt.show()
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