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Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
import numpy as np
df = pd.DataFrame({
'A': [1, np.nan, 3],
'B': ['x', 'y', np.nan]
})
for k,v in df.to_dict()['A'].items():
print(f"v={v},type(v)={type(v)}")
print("pd-v:",pd.__version__)
print( df.to_dict()['A'][1] is None)
print( df.to_dict()['A'][1] is np.nan)
print(df.to_dict()['A'][1])
print(type(df.to_dict()['A'][1]))
print(np.isnan(df.to_dict()['A'][1]))
#--------------
# v=1.0,type(v)=<class 'float'>
# v=nan,type(v)=<class 'float'>
# v=3.0,type(v)=<class 'float'>
# pd-v: 2.2.3
# False
# False
# nan
# <class 'float'>
# TrueIssue Description
BUG: to_dict(orient='dict') does not convert np.nan to None in Pandas 2.2.3
Expected Behavior
NaN --> None
Installed Versions
Replace this line with the output of pd.show_versions()
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IO issues that don't fit into a more specific labelIO issues that don't fit into a more specific labelClarification about behavior needed to assess issueClarification about behavior needed to assess issue