Vectorised Method To Append Dataframe Rows To Columns And Vice-versa
My dataframe is as follows: df = pd.DataFrame({'a': {'d': 1, 'e': 0, 'f': 1, 'g': 1}, 'b': {'d': 0, 'e': 0, 'f': 0, 'g': 1}, 'c': {'d': 0, 'e'
Solution 1:
Here's one way using reindex
:
(df.reindex(df.columns.append(df.index),
axis=1,
fill_value =0)
.reindex(df.index.append(df.columns),
axis=0,
fill_value =0))
print(df_new)
ab c d e f g
d 1000000
e 0010000
f 1010000
g 1100000a0000000b0000000
c 0000000
Solution 2:
Use DataFrame.reindex
witn columns
and index
parameter, new values should be created by Index.append
:
df1 = df.reindex(columns=df.columns.append(df.index),
index=df.index.append(df.columns),
fill_value = 0)
print (df1)
a b c d e f g
d 1000000
e 0010000
f 1010000
g 1100000
a 0000000
b 0000000
c 0000000
Or by Index.union
:
df1 = df.reindex(columns=df.columns.union(df.index, sort=False),
index=df.index.union(df.columns, sort=False),
fill_value = 0)
print (df1)
a b c d e f g
a 0000000
b 0000000
c 0000000
d 1000000
e 0010000
f 1010000
g 1100000
Solution 3:
Create a dictionary from fromkeys
then unpack it, then use assign
and T
then assign
then T
:
print(df.assign(**dict.fromkeys(df.index, 0)).T.assign(**dict.fromkeys(df.columns, 0)).T)
Output:
ab c d e f g
d 1000000
e 0010000
f 1010000
g 1100000a0000000b0000000
c 0000000
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