How can I list sequentially the x and y axis on chart?

Question

I have a dataframe and I want to show them on graph. When I start my code, the x and y axis are non-sequential. How can I solve it? Also I give a example graph on picture. First image is mine, the second one is what I want.

This is my code:

from datetime import timedelta, date
import datetime as dt #date analyse
import matplotlib.pyplot as plt
import pandas as pd #read file

def daterange(date1, date2):
    for n in range(int ((date2 - date1).days)+1):
        yield date1 + timedelta(n)
tarih="01-01-2021"
tarih2="20-06-2021"
start=dt.datetime.strptime(tarih, '%d-%m-%Y')
end=dt.datetime.strptime(tarih2, '%d-%m-%Y')
fg=pd.DataFrame()
liste=[]
tarih=[]
for dt in daterange(start, end):
    dates=dt.strftime("%d-%m-%Y")
    with open("fng_value.txt", "r") as filestream:
            for line in filestream:
                date = line.split(",")[0]
                if dates == date:
                    fng_value=line.split(",")[1]
                    liste.append(fng_value)
                    tarih.append(dates)
fg['date']=tarih
fg['fg_value']=liste
print(fg.head())
plt.subplots(figsize=(20, 10))
plt.plot(fg.date,fg.fg_value)
plt.title('Fear&Greed Index')
plt.ylabel('Fear&Greed Data')
plt.xlabel('Date')
plt.show()

This is my graph:

This is the graph that I want:

Answer 1

Line plot with datetime x axis

So it appears this code is opening a text file, adding values to either a list of dates or a list of values, and then making a pandas dataframe with those lists. Finally, it plots the date vs values with a line plot.

A few changes should help your graph look a lot better. A lot of this is very basic, and I'd recommend reviewing some matplotlib tutorials. The Real Python tutorial is a good starting place in my opinion.

Fix the y axis limit:

plt.set_ylim(0, 100)

Use a x axis locator from mdates to find better spaced x label locations, it depends on your time range, but I made some data and used day locator.

import matplotlib.dates as mdates
plt.xaxis.set_major_locator(mdates.DayLocator())

Use a scatter plot to add data points as on the linked graph

plt.scatter(x, y ... )

Add a grid

plt.grid(axis='both', color='gray', alpha=0.5)

Rotate the x tick labels

plt.tick_params(axis='x', rotation=45)

I simulated some data and plotted it to look like the plot you linked, this may be helpful for you to work from.

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.dates as mdates

fig, ax = plt.subplots(figsize=(15,5))

x = pd.date_range(start='june 26th 2021', end='july 25th 2021')
rng = np.random.default_rng()
y = rng.integers(low=15, high=25, size=len(x))

ax.plot(x, y, color='gray', linewidth=2)
ax.scatter(x, y, color='gray')

ax.set_ylim(0,100)
ax.grid(axis='both', color='gray', alpha=0.5)
ax.set_yticks(np.arange(0,101, 10))
ax.xaxis.set_major_locator(mdates.DayLocator())
ax.tick_params(axis='x', rotation=45)
ax.set_xlim(min(x), max(x))