Reputation: 456
I was going through a tutorial on Pandas. I decided to experiment halfway with what I thought should be straight forward. I condensed it to a simple code for others to reproduce personally and help me see what is my error or the error in Python.
df = pd.DataFrame({'A': 1.,
'B': pd.Timestamp('20130102'),
'C': pd.Series(1, index = list(range(4)), dtype = 'float32'),
'D': np.array([3] * 4, dtype = 'int32'),
'E': pd.Categorical(["test", "train", "test", "train"]),
'F': 'foo'
})
# Made copy of df and modified it individually to show that it works.
df2 = df
df2.drop([1,3], inplace=True) # Dropping 2nd and 5th row.
print(df2)
# Now trying to do the same for multiple dataframes in a
# dictionary keeps giving me an error.
dic = {'1900' : df, '1901' : df, '1902' : df} # Dic w/ 3 pairs.
names = ['1900', '1901', '1902'] # The dic keys in list.
# For loop to drop the 2nd and 4th row.
for ii in names:
df_dic = dic[str(ii)]
df_dic.drop([1,3], inplace=True)
dic[str(ii)] = df_dic
The output I get is:
A B C D E F
0 1.0 2013-01-02 1.0 3 test foo
2 1.0 2013-01-02 1.0 3 test foo
--------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-139-8236a9c3389e> in <module>()
21 for ii in names:
22 df_dic = dic[str(ii)]
---> 23 df_dic.drop([1,3], inplace=True)
C:\Anaconda3\lib\site-packages\pandas\core\generic.py in drop(self, labels, axis, level, inplace, errors)
1905 new_axis = axis.drop(labels, level=level, errors=errors)
1906 else:
-> 1907 new_axis = axis.drop(labels, errors=errors)
1908 dropped = self.reindex(**{axis_name: new_axis})
1909 try:
C:\Anaconda3\lib\site-packages\pandas\indexes\base.py in drop(self, labels, errors)
3260 if errors != 'ignore':
3261 raise ValueError('labels %s not contained in axis' %
-> 3262 labels[mask])
3263 indexer = indexer[~mask]
3264 return self.delete(indexer)
ValueError: labels [1 3] not contained in axis
So obviously the dropping the rows when doing it individually works since it gave me the desired output. Why is implementing in a For Loop
making it behave strangely?
Thanks in advance.
Upvotes: 2
Views: 1479
Reputation: 863801
You need copy
DataFrame
:
for ii in names:
df_dic = dic[str(ii)].copy()
df_dic.drop([1,3], inplace=True)
dic[str(ii)] = df_dic
print (dic)
{'1900': A B C D E F
0 1.0 2013-01-02 1.0 3 test foo
2 1.0 2013-01-02 1.0 3 test foo, '1902': A B C D E F
0 1.0 2013-01-02 1.0 3 test foo
2 1.0 2013-01-02 1.0 3 test foo, '1901': A B C D E F
0 1.0 2013-01-02 1.0 3 test foo
2 1.0 2013-01-02 1.0 3 test foo}
Upvotes: 2