Pandas_[‘index‘]_is_not_found_in_axis

在 pandas 表格操作中，很容易多出一列 ‘index’ 列，drop 也 drop 不掉。

问题：
In pandas, after reset_index(), it emerges a new ‘index’ col, but I don’t want it. When I try df.drop(‘index’, axis=1), it tells me [‘index’] not found in axis. I don’t want this ‘index’ col!

whenever doing:
df = df.reset_index()
df = df.rename(columns={‘xx’: ‘yy’})
df = df.sort_values(by=‘xxx’, ascending=False, inplace=True)
When I enter inplace=True or not, or using df = or not, it will show me a new ‘index’ col that I can’t drop.

建议：

When you use reset_index() in pandas, it adds a new column called index by default, which contains the old index values. If you want to drop this new index column after resetting the index, you should use the drop() method with the inplace=True parameter to modify the DataFrame in place, or you can assign the result to a new variable.

Here’s how you can do it:

import pandas as pd

# Example DataFrame
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
}, index=['x', 'y', 'z'])

# Reset the index and drop the old index column
df_reset = df.reset_index().drop('index', axis=1)

# Print the resulting DataFrame
print(df_reset)

In this example, df.reset_index() resets the index and creates a new column called index. The drop(‘index’, axis=1) method is then called on the result of reset_index() to remove the index column. The axis=1 parameter specifies that you want to drop a column, as opposed to axis=0 which would drop a row.

If you want to modify the original DataFrame without creating a new one, you can use inplace=True:

# Reset the index and drop the old index column in place
df.reset_index(drop=True)

By setting drop=True in the reset_index() method, you tell pandas not to add the old index as a column, thus avoiding the need to drop it afterward.