I have a pandas DataFrame that need to be fed in chunks of n-rows into downstream functions (print in the example). The chunks may have overlapping rows.
Use DataFrame.groupby with integer division with helper 1d array created with same length like df - index values are not overlapped:
d = {'A':list(range(5)), 'B':list(range(5))}
df=pd.DataFrame(d)
print (np.arange(len(df)) // 2)
[0 0 1 1 2]
for i, g in df.groupby(np.arange(len(df)) // 2):
print (g)
A B
0 0 0
1 1 1
A B
2 2 2
3 3 3
A B
4 4 4
EDIT:
For overlapping values is edited this answer:
def chunker1(seq, size):
return (seq.iloc[pos:pos + size] for pos in range(0, len(seq)-1))
for i in chunker1(df,2):
print (i)
A B
0 0 0
1 1 1
A B
1 1 1
2 2 2
A B
2 2 2
3 3 3
A B
3 3 3
4 4 4
A generator version of the chunk function with step parameter for control overlapping factor is presented below. Moreover this version works with custom index of the pd.DataFrame or pd.Series (e.g. float type index). For more convenience (to check overlapping), the integer index is used here.
sz = 14
# ind = np.linspace(0., 10., num=sz)
ind = range(sz)
df = pd.DataFrame(np.random.rand(sz,4),
index=ind,
columns=['a', 'b', 'c', 'd'])
def chunker(seq, size, overlap):
for pos in range(0, len(seq), size-overlap):
yield seq.iloc[pos:pos + size]
chunk_size = 6
chunk_overlap = 2
for i in chunker(df, chunk_size, chunk_overlap):
print(i)
chnk = chunker(df, chunk_size, chunk_overlap)
print('\n', chnk, end='\n\n')
print('First "next()":', next(chnk), sep='\n', end='\n\n')
print('Second "next()":', next(chnk), sep='\n', end='\n\n')
print('Third "next()":', next(chnk), sep='\n', end='\n\n')
The output for the overlapping size = 2
a b c d
0 0.577076 0.025997 0.692832 0.884328
1 0.504888 0.575851 0.514702 0.056509
2 0.880886 0.563262 0.292375 0.881445
3 0.360011 0.978203 0.799485 0.409740
4 0.774816 0.332331 0.809632 0.675279
5 0.453223 0.621464 0.066353 0.083502
a b c d
4 0.774816 0.332331 0.809632 0.675279
5 0.453223 0.621464 0.066353 0.083502
6 0.985677 0.110076 0.724568 0.990237
7 0.109516 0.777629 0.485162 0.275508
8 0.765256 0.226010 0.262838 0.758222
9 0.805593 0.760361 0.833966 0.024916
a b c d
8 0.765256 0.226010 0.262838 0.758222
9 0.805593 0.760361 0.833966 0.024916
10 0.418790 0.305439 0.258288 0.988622
11 0.978391 0.013574 0.427689 0.410877
12 0.943751 0.331948 0.823607 0.847441
13 0.359432 0.276289 0.980688 0.996048
a b c d
12 0.943751 0.331948 0.823607 0.847441
13 0.359432 0.276289 0.980688 0.996048
First "next()":
a b c d
0 0.577076 0.025997 0.692832 0.884328
1 0.504888 0.575851 0.514702 0.056509
2 0.880886 0.563262 0.292375 0.881445
3 0.360011 0.978203 0.799485 0.409740
4 0.774816 0.332331 0.809632 0.675279
5 0.453223 0.621464 0.066353 0.083502
Second "next()":
a b c d
4 0.774816 0.332331 0.809632 0.675279
5 0.453223 0.621464 0.066353 0.083502
6 0.985677 0.110076 0.724568 0.990237
7 0.109516 0.777629 0.485162 0.275508
8 0.765256 0.226010 0.262838 0.758222
9 0.805593 0.760361 0.833966 0.024916
Third "next()":
a b c d
8 0.765256 0.226010 0.262838 0.758222
9 0.805593 0.760361 0.833966 0.024916
10 0.418790 0.305439 0.258288 0.988622
11 0.978391 0.013574 0.427689 0.410877
12 0.943751 0.331948 0.823607 0.847441
13 0.359432 0.276289 0.980688 0.996048