如何去除Pandas查询结果中的dtype: float64及解决相关报错

Hey Christopher, let's break down and fix each of your issues step by step!

1. Removing the dtype: float64 from your average output #

When you print a Pandas Series (which is what IrisData.mean(axis=0) returns), it automatically includes the dtype info at the bottom. To get rid of this, you have a few simple options:

Option 1: Convert to a string without dtype #

Use the to_string() method of the Series, which omits the dtype line entirely:

print(averageofdata.to_string())

Option 2: Format output manually (for better readability) #

If you want more control over how averages are displayed (like rounding to 2 decimal places), loop through the Series items to print each value with context:

print("Average Sizes of All Iris Data")
for column, avg_value in averageofdata.items():
    print(f"{column}: {avg_value:.2f}")

2. Fixing the 37m prefix in print output #

That 37m is part of an ANSI escape code (specifically for white text color). This usually pops up if your terminal/IDE has auto-color formatting enabled, or if there's accidental escape code leakage in your environment. Here's how to clean it up:

Quick fix: Filter out the escape code #

If you just want to strip the 37m from your output, remove it when converting the Series to a string:

clean_output = str(averageofdata).replace('\033[37m', '')
print(clean_output)

Root cause check #

If this keeps happening, double-check that you haven't imported any color-related libraries (like colorama) that might be modifying output, or adjust your terminal's color settings to disable auto-formatting if needed.

3. Fixing the AttributeError with loadtxt #

The error module 'pandas' has no attribute 'loadtxt' makes total sense—loadtxt is a NumPy function, not a Pandas one!

On top of that, the Iris dataset includes a non-numeric column (species, with strings like "setosa"), so using numpy.loadtxt() with dtype='float' would fail anyway—it can't handle mixed data types.

Stick with your original pd.read_csv() code! It's built to handle mixed-type CSV files perfectly, which is exactly what the Iris dataset is:

IrisData = pd.read_csv('IRIS.csv')

内容的提问来源于stack exchange，提问作者Christopher