preamble
In practice, you occasionally encounter situations such as using Pandas to calculate the following correlation coefficients and writing the results to an Excel file.
correlations = (method='pearson',min_periods=1) # Calculate the matrix of correlation coefficients between features
correlations.to_excel('')
When the Excel file is read again, columns appear without column names.
import pandas as pd
correlations= pd.read_excel('')
correlations
No column names generally means that there are no column names in the original table, but there are column names when read out by pandas, and the general naming convention is.
Unnamed:x
x- denotes the xth column that is unnamed or renamed.
How can I delete this column with no column name?
Method 1: Leave normal columns by filtering them.
print()
col = ()
('Unnamed: 0')
print(col)
correlations1 = correlations[col]
correlations1
Index(['Unnamed: 0', 'Recent Balance Ratio', 'Customer Membership Days', 'Cumulative Spending', 'Interval Days Slope', 'Interval Time Standard Deviation',
'Days Between Recent Transactions', 'Balance Slope', 'Balance Standard Deviation', 'Consumption Ratio in Recent Months'],
dtype='object')
['Recent Balance Ratio', 'Customer Membership Days', 'Cumulative Spending', 'Interval Days Slope', 'Interval Time Standard Deviation', 'Days Between Recent Transactions'.
'Balance slope', 'Balance standard deviation', 'Consumption ratio in recent months']
Method 2: Delete the column directly.
correlations2 = (columns='Unnamed: 0') correlations2
The results are the same as above, slightly.
pandas removes columns that contain certain characters in the column name
>>> df = df[(list((regex='Test')))]
summarize
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