for loop to get the dataframe in pandas

user_14944419 0
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i am trying to get certain data in a dataframe using for loop. But when i run the loop all i get is the index of the data not the values presented in the rows

import pandas as pd
import numpy as np

data = {'time' : [1,2,3,4,5,6,7,8,9,10,11,12], 'values'[290,260,288,300,310,303,329,340,316,330,308,310]}

df = pd.DataFrame(data)

for i in df:

    print(i)

I only get the index not the values

I also tried:

for index , values in df:

    print(values)

It gives me this error: cannot unpack non-iterable int object

I know iterrows give me rows but i want it as a complete dataframe not each rows

python-3.7 pandas python
3 Answers

try use DataFrame.iterrows() :

for index,row in df.iterrows():
    
    print(row)
    # each row is a pd.Series object so to access any values call row['column_name']
    time,value = row['time'],row['value']
    print(time,value)

Note: anyway i want to comment that it is not advised to use this type of operations in pandas because it is a nonvectorized solution which lack in performance in comparison to vectorized operations, I suggest you to look for vectorization in the internet... good luck :)

user_88938270

You can also use df.values to iterate over the DataFrame

import pandas as pd
import numpy as np

data = {'time' : [1,2,3,4,5,6,7,8,9,10,11,12], 'values':[290,260,288,300,310,303,329,340,316,330,308,310]}

df = pd.DataFrame.from_dict(data)

>>> for i in df.values:
...     print(i)
...
[  1 290]
[  2 260]
[  3 288]
[  4 300]
[  5 310]
[  6 303]
[  7 329]
[  8 340]
[  9 316]
[ 10 330]
[ 11 308]
[ 12 310]

Further you can filter the required rows based on the indexes of the columns

user_91089120

Try using this:

for ind in df.index:
     print(list(df[col][ind] for col in df.columns))

This piece of code prints the data row-wise

user_147929160
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