All Questions
411
questions
1
vote
1
answer
56
views
Reshape Pandas Dataframe and group by 2 level columns
I have a dataframe with flat structure of having unique Rows as follow.
I need to reshape it as shown below.
Using Pivot table and swapping levels, I managed to obtain somewhat closer to the result, ...
0
votes
1
answer
46
views
this code show an reshape error. how fix this?
I'm new in python and ML. I wrote this code for practicing. It displays this error. how do I solve this reshape problem?
import pandas as pd
import sklearn as skl
data=pd.read_csv('housing.csv')
...
0
votes
0
answers
48
views
Pandas move levels of a composite column as a value
Let's imagine as a starting point I have a dataframe, similar to the one below (using a tuple for the composite columns):
Index, (ATop,AMiddle,ABottom,filt1_1, filt2_1), (ATop,AMiddle,ABottom,filt1_2,...
0
votes
1
answer
42
views
cannot reshape array of size 4 into shape (4,4) in DataFrame where clause
Can anyone explain to me what is going on? Here's the piece of code. If I have the DataFrame of precisely length 4, the statement in the try clause throws an exception. If I make the dataframe of any ...
0
votes
0
answers
43
views
Is there a more effective way to create new columns from row values in a Pandas DataFrame? [duplicate]
Given a dataframe with three initial columns, one of which has categorical type with two categories, the aim is to create distinct columns for each category and subsequently store within them the ...
1
vote
3
answers
143
views
Reshape a stacked style data file into a dataframe using pandas
I have a csv input file with the below format and i'm looking for a fairly easy way to convert to normal shape dataframe in pandas. the csv data file has all data stacked up into two columns with each ...
-1
votes
1
answer
152
views
ValueError: Expected 2D array
I try to make a SVC.
from sklearn.svm import SVC
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv("iris.csv")
df.loc[df["species"]=="...
0
votes
1
answer
68
views
reshape problem in LogisticRegression code
I try to make a LogisticRegression.
import pandas
import matplotlib.pyplot as plt
from sklearn.linear_model import LogisticRegression
import numpy as np
df = pd.read_csv("tested.csv")
df....
0
votes
1
answer
90
views
reshaping rows and columns and then converting to numpy array
Following DataFrame contains integer values. I want them to reshaped into a new column where every row will be represented, as a combination of each 3 rows of each columns from old dataframe.
import ...
0
votes
2
answers
112
views
fit function expected 2D array, got 1D array instead
I am using Linear Regression to predict the 'Value' throughout the years, I have the following data, i imported from a csv file :
**df.head()** :
LOCATION INDICATOR SUBJECT MEASURE FREQUENCY ...
0
votes
1
answer
105
views
How can I rearrange df as the nodes index in pytorch geometric manner?
I'd like to rearrange my dataframe (data) as the node index to the original name in pytorch geometric manner for extracting node embedding.
import pandas as pd
data = {'Source': ['Rainfall', 'SP2', '...
0
votes
0
answers
39
views
Reshape/Reposition dataframe using pandas [duplicate]
I have a dataframe df as following:
I want to reshape/reposition from df into df2 as following:
I have tried, but it gave a strange result (please see my code)
Appreciate any suggestions here.
# ...
0
votes
2
answers
79
views
Narrow to wide data
I have a following Data frame (df) as shown below:
Is it possible to reshape my (df) into (df1) as shown below:
I have provided a sample of my code, but it does not work.
Appreciate any through or ...
1
vote
3
answers
58
views
to check the values of different and columns and if matching then assigned to the rows
Suppose I have the following columns for a dataframe (1, 2, 3, 4):
Column1 value: ('Curl Care Anti-Hairfall 200ml', 'Curl Care Clean 200ml', 'Curl Care Color Protect 200ml')
Column2 value: ('Curl ...
1
vote
3
answers
72
views
Reshaping a Dataframe with repeating column names
I have data that looks like this:
dataframe_1:
week SITE LAL SITE LAL
0 1 BARTON CHAPEL 1.1 PENASCAL I 1
1 2 BARTON CHAPEL 1.1 PENASCAL I 1
2 3 ...