如何获得正确的轴 matplotlib

Question

I have this table and I want to display two trends vs the date. I want to show the close of the stock prices from the table along with the oil prices. For some reason, I'm really struggling to do this. Here's what I've done so far:

As you can clearly see, this is not what I'm going for... I don't know why my y axis appears this way and I just want to lines displaying these columns with the y axis as price. Can someone help?

Here is the result of the info command on this table.

<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 91 entries, 2010-02-01 to 2020-09-01
Data columns (total 7 columns):
 #   Column     Non-Null Count  Dtype  
---  ------     --------------  -----  
 0   Open       91 non-null     float64
 1   High       91 non-null     float64
 2   Low        91 non-null     float64
 3   Close      91 non-null     float64
 4   Adj Close  91 non-null     float64
 5   Volume     91 non-null     int64  
 6   Oil Price  91 non-null     object 
dtypes: float64(5), int64(1), object(1)
memory usage: 8.2+ KB

Answer 1

Answer

As you can see from the output of stocksAndOil.info() , the column Close is float64 type and this is fine: pandas interprets its values as numbers.
On the contrary, the column Oil Price is object : this means pandas interprets its values as string, not numbers. In other words, the value 74.41 for Oil price at 2020-02-01 (first row of the screenshot above) is interpreted as the string '74.41' .
To solve, you need to convert Oil price column type from str to float with:

stocksAndOil['Oil price'] = stocksAndOil['Oil price].astype(float)

Example

Check this code as an example:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'A': [1, 2, 3],
                   'B': ['3', '2', '4']})

print(df.info())

fig, ax = plt.subplots()

ax.scatter(df['A'], df['B'])

plt.show()

As you can se the column 'B' has only str values. The output of df.info() is:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 2 columns):
 #   Column  Non-Null Count  Dtype 
---  ------  --------------  ----- 
 0   A       3 non-null      int64 
 1   B       3 non-null      object
dtypes: int64(1), object(1)
memory usage: 100.0+ bytes

Ans the resulting plot is:

Check the y axis labels: 2 is between 3 and 4 , so this is clearly wrong.
To solve I use this code:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'A': [1, 2, 3],
                   'B': ['3', '2', '4']})
df['B'] = df['B'].astype(float)

print(df.info())

fig, ax = plt.subplots()

ax.scatter(df['A'], df['B'])

plt.show()

The output of df.info() is:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 2 columns):
 #   Column  Non-Null Count  Dtype  
---  ------  --------------  -----  
 0   A       3 non-null      int64  
 1   B       3 non-null      float64
dtypes: float64(1), int64(1)
memory usage: 112.0 bytes

This time the 'B' column has float values and the resulting plot is correct: