How to correct overlapping tick labels in matplotlib plot

Question

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.

for example, the first graph should be a curly line, however, I got a straight line plotted in the graph.

I wonder how to plot these lines correctly? and fix both axis?

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()

Answer 1

1. The dates are not a datetime format, so they are interpreted as strings, and they're all unique, which makes a mess of the axis.
   • df.index = pd.to_datetime(df.index) has been added
2. The values in the columns are also strings, not numbers
   • 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
   • print(df.info()) has been added. Review and fix any column that is an object. That means the column contains some strings and can't be converted to a float.
     • Use [np.nan] instead of ['No Data'], so the column can be set as a float, which will allow it to plot correctly.

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()