Pandas 1.3 >>>importpandasaspd>>>importnumpyasnp>>>df=pd.DataFrame([0.5,np.nan])>>>df.where(pd.notnull(df),None)000.51NaN Problem description Replacing NaN values with None (or any other Python object) should w
When replacing values in a categorical series with NA, I see the error "boolean value of NA is ambiguous". Expected Behavior If we replace with NumPy's NaN value instead of pandas' NA, it works as expected. import numpy as np import pandas as pd phonetic = pd.DataFrame({ "x": ["al...
Table 2: Show alignment of X features to the predicted future values under ‘Predict This’ A simple minded python loop centric way of creating this label column for y, is as follows: import pandas as pd import matplotlib.pyplot as plt import numpy as np df = pd...
Python - replace multiple values in a column and keep, I need to replace red with 1 and blue with 2, leaving orange as it is, in the column name. I use map function like below: df.name.map({'red': 0, 'blue': 1}) I got result like: name value 0 0.0 22 1 NaN 44 2 1.0 ...