Here is an example using matplotlib.dates for formatting a custom datetime-formatted x-axis using seaborn

• 每一月的刻度都被(新的)年而不是月所取代
• ConciseDateFormatter用于自动缩写月份

例如，:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

# Sample data
df_tagesspiegel_final = pd.DataFrame(
    {
        "Datum": [
            "20220101",
            "20220115",
            "20220221",
            "20220610",
            "20220903",
            "20221016",
            "20230201",
            "20230215",
        ],
        "compound": [0.11, 0.21, 0.3, 0.25, 0.47, 0.32, 0.48, 0.5],
    }
)

df_tagesspiegel_final["Datum2"] = pd.to_datetime(
    df_tagesspiegel_final["Datum"], format="%Y%m%d"
)

# Scatterplot construction
fig, ax = plt.subplots(figsize=(6, 4), dpi=150)
sns.scatterplot(
    x="Datum2", y="compound", data=df_tagesspiegel_final, ax=ax, zorder=2
)

# Set the locators for the x-axis
months = mdates.MonthLocator()  # Every month
years = mdates.YearLocator()  # Every year

# Get current axes ("gca")
ax = plt.gca()

ax.xaxis.set_major_locator(months)
ax.xaxis.set_minor_locator(years)

# Set the date format
ax.xaxis.set_major_formatter(mdates.ConciseDateFormatter(months))

# Display the plot
plt.grid(
    True, which="both", linestyle="--", linewidth=0.5, zorder=1, alpha=0.5
)
plt.xlabel("Datum")
plt.ylabel("compound")
plt.title("Compound-Sentiment im Zeitverlauf")
plt.show()

# Show data structure of sample data
print(df_tagesspiegel_final)
print(df_tagesspiegel_final.info())

提供:

      Datum  compound     Datum2
0  20220101      0.11 2022-01-01
1  20220115      0.21 2022-01-15
2  20220221      0.30 2022-02-21
3  20220610      0.25 2022-06-10
4  20220903      0.47 2022-09-03
5  20221016      0.32 2022-10-16
6  20230201      0.48 2023-02-01
7  20230215      0.50 2023-02-15

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 8 entries, 0 to 7
Data columns (total 3 columns):
 #   Column    Non-Null Count  Dtype         
---  ------    --------------  -----         
 0   Datum     8 non-null      object        
 1   compound  8 non-null      float64       
 2   Datum2    8 non-null      datetime64[ns]
dtypes: datetime64[ns](1), float64(1), object(1)
memory usage: 320.0+ bytes
None