Empty copy of Pandas DataFrame

user_169947 0
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I'm looking for an efficient idiom for creating a new Pandas DataFrame with the same columns and types as an existing DataFrame, but with no rows. The following works, but is presumably much less efficient than it could be, because it has to create a long indexing structure and then evaluate it for each row. I'm assuming that's O(n) in the number of rows, and I would like to find an O(1) solution (that's not too bad to look at).

out = df.loc[np.repeat(False, df.shape[0])].copy()

I have the copy() in there because I honestly have no idea under what circumstances I'm getting a copy or getting a view into the original.

For comparison in R, a nice idiom is to do df[0,], because there's no zeroth row. df[NULL,] also works.

pandas dataframe indexing
4 Answers

I think the equivalent in pandas would be slicing using iloc

df = pd.DataFrame({'A' : [0,1,2,3], 'B' : [4,5,6,7]})
print(df1)
   A  B
0  0  4
1  1  5
2  2  6
3  3  7

df1 = df.iloc[:0].copy()

print(df1)
Empty DataFrame
Columns: [A, B]
Index: []
user_93751020

Df1 the existing DataFrame:

df1 = pd.DataFrame({'x1':[1,2,3], 'x2':[4,5,6]})

Df2 the new, based on the columns in df1:

df2 = pd.DataFrame({}, columns=df1.columns)

For setting the dtypes of the different columns:

for x in df1.columns:
    df2[x]=df2[x].astype(df1[x].dtypes.name)
user_40086570

Update no rows

Use reindex:

dfcopy = pd.DataFrame().reindex(columns=df.columns)
print(dfcopy)

Output:

Empty DataFrame
Columns: [a, b, c, d, e]
Index: []

We can use reindex_like.

dfcopy = pd.DataFrame().reindex_like(df)

MCVE:

#Create dummy source dataframe
df = pd.DataFrame(np.arange(25).reshape(5,-1), index=[*'ABCDE'], columns=[*'abcde'])

dfcopy = pd.DataFrame().reindex_like(df)
print(dfcopy)

Output:

    a   b   c   d   e
A NaN NaN NaN NaN NaN
B NaN NaN NaN NaN NaN
C NaN NaN NaN NaN NaN
D NaN NaN NaN NaN NaN
E NaN NaN NaN NaN NaN
user_63615310

Please deep copy original df and drop index.

#df1=(df.copy(deep=True)).drop(df.index)#If df is small
df1=df.drop(df.index).copy()#If df is large and dont want to copy and discard
user_89869750
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