将数据转换为 pandas DataFrame 并删除一些

Question

我有一个测量数据集要转换成浮点值数据帧。但有时机器不测量并设置一个“---”字符，导致 pandas.to_numeric ValueError。对于此处的简化示例，我的问题是如何转换为浮动孔列并删除我有字符串“---”字符集的位置：

data = {'row_1': ["3.0", "2.4", "---", "0.0"], 'row_2': ['a', 'b', 'c', 'd']}
df = pandas.DataFrame.from_dict(data)

如何删除整个第三行并将 row_1 值转换为浮点数？谢谢

Answer 1

尝试这样的事情

import pandas as pd
data = {'row_1': ["3.0", "2.4", "---", "0.0"], 'row_2': ['a', 'b', 'c', 'd']}
df = pd.DataFrame.from_dict(data)

df = df[df['row_1']!='---'].copy()
df['row_1'] = df['row_1'].astype(float)

Answer 2

# Convert to floating point, but first make sure triple dashes can be interpreted as NaNs
df['row_1'] = df['row_1'].replace('---', 'NaN').astype(float)

# drop rows with NaNs
df = df.dropna()

将数据转换为 pandas DataFrame 并删除一些

Convert data into a pandas DataFrame and remove some

python

dataframe

pandas

autonumeric.js