The problem is in the line
df = df.set_index('Date',inplace=True)
Either remove inplace=True, or remove the assignment df =, leaving just
df.set_index('Date',inplace=True)
The same goes for the next line. Either use inplace=True, or assign the new dataframe to df, not both.
Answer from Ivan Gorin on Stack OverflowBUG: groupby.agg fails when input has duplicate columns and dict input
'DataFrame' object has no attribute 'name' when trying to delete specific rows in a csv file
python - DataFrame object has no attribute 'name' - Stack Overflow
python - How to resolve AttributeError: 'DataFrame' object has no attribute - Stack Overflow
The problem is in the line
df = df.set_index('Date',inplace=True)
Either remove inplace=True, or remove the assignment df =, leaving just
df.set_index('Date',inplace=True)
The same goes for the next line. Either use inplace=True, or assign the new dataframe to df, not both.
When you specify inplace=True and want to see it's contents, it would return None as they merely mutate the DF instead of creating a new copy of it. Basically, you're assigning None to the result and hence it complains of the AttributeError as it isn't a df.DataFrame object anymore to access it's .head() method.
You can do it now in two ways:
No assigning with inplace parameter
df.rename(columns={'Adj Close': ticker},inplace=True)
assign without inplace parameter
df= df.rename(columns={'Y':l})
It claims that the error revolves around df = df[df.name != "gif"], even though rows with those characters are exactly what I'm trying to delete.
import pandas as pd
df = pd.read_csv("Output Configured 3 edit.csv")
df = df[df.name != "gif"]
# df.column_name != whole string from the cell
# now, all the rows with the column: Name and Value: "dog" will be deleted
df.to_csv(file, index=False)the solution is to use a loc to set the values, rather than creating a copy.
creating a copy of df loses the name:
df = df[::-1] # creates a copy
setting the value 'keeps' the original object intact, along with name
df.loc[:] = df[:, ::-1] # reversal maintaining the original object
Example code that reverses values along the column axis:
df = pd.DataFrame([[6,10]], columns=['a','b'])
df.name='t'
print(df.name)
print(df)
df.iloc[:] = df.iloc[:,::-1]
print(df)
print(df.name)
outputs:
t
a b
0 6 10
a b
0 10 6
t
A workaround is to set a columns.name and use it when needed.
Example:
df = pd.DataFrame()
df.columns.name = 'name'
print(df.columns.name)
name
Check your DataFrame with data.columns
It should print something like this
Index([u'regiment', u'company', u'name',u'postTestScore'], dtype='object')
Check for hidden white spaces..Then you can rename with
data = data.rename(columns={'Number ': 'Number'})
I think the column name that contains "Number" is something like " Number" or "Number ". I'm assuming you might have a residual space in the column name. Please run print "<{}>".format(data.columns[1]) and see what you get. If it's something like < Number>, it can be fixed with:
data.columns = data.columns.str.strip()
See pandas.Series.str.strip
In general, AttributeError: 'DataFrame' object has no attribute '...', where ... is some column name, is caused because . notation has been used to reference a nonexistent column name or pandas method.
pandas methods are accessed with a .. pandas columns can also be accessed with a . (e.g. data.col) or with brackets (e.g. ['col'] or [['col1', 'col2']]).
data.columns = data.columns.str.strip() is a fast way to quickly remove leading and trailing spaces from all column names. Otherwise verify the column or attribute is correctly spelled.
wine = pd.read_csv("combined.csv", header=0).iloc[:-1]
df = pd.DataFrame(wine)
df
dataset = pd.DataFrame(df.data, columns =df.feature_names)
dataset['target']=df.target
datasetERROR:
<ipython-input-27-64122078da92> in <module>
----> 1 dataset = pd.DataFrame(df.data, columns =df.feature_names)
2 dataset['target']=df.target
3 dataset
D:\Anaconda\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
5463 if self._info_axis._can_hold_identifiers_and_holds_name(name):
5464 return self[name]
-> 5465 return object.__getattribute__(self, name)
5466
5467 def __setattr__(self, name: str, value) -> None:
AttributeError: 'DataFrame' object has no attribute 'data'I'm trying to set up a target to proceed with my Multi Linear Regression Project, but I can't even do that. I've already downloaded the CSV file and have it uploaded on a Jupyter Notebook. What I'm I doing wrong?
The original question was posted a long time ago, but I just came across the same issue and found the solution here: pd.read_html() imports a list rather than a dataframe
When you do pd.read_html you are creating a list of dataframes since the website may have more than 1 table. Add one more line of code before you try your rename:
dfs = pd.read_html(url, header=0)
and then df = dfs[0] ; you will have the df variable as a dataframe , which will allow you to run the df.rename command you are trying to run in the original question.
this should be able to fix , df is you dataset df.columns=['a','b','c','d','e','f']
I am in university and am taking a special topics class regarding AI. I have zero knowledge about Python, how it works, or what anything means.
A project for the class involves manipulating Bayesian networks to predict how many and which individuals die upon the sinking of a ship. This is the code I am supposed to manipulate:
##EDIT VARIABLES TO THE VARIABLES OF INTEREST
train_var = train.loc[:,['Survived','Sex']]
test_var = test.loc[:,['Sex']]
BayesNet = BayesianModel([('Sex','Survived')])I am supposed to add another variable, 'Pclass,' to the mix, paying attention to the order for causation. I have added that variable to every line of this code in every way imaginable and consistently get an error from this line:
predictions = pandas.DataFrame({'PassengerId': test.PassengerId,'Survived': hypothesis.Survived.tolist()})
predictionsFor example, the error I get for this version of the code:
train_var = train.loc[:,['Survived','Pclass','Sex']]
test_var = test.loc[:,['Pclass']]
BayesNet = BayesianModel([('Sex','Pclass','Survived')])is this:
AttributeError Traceback (most recent call last)
<ipython-input-98-16d9eb9451f7> in <module>
----> 1 predictions = pandas.DataFrame({'PassengerId': test.PassengerId,'Survived': hypothesis.Survived.tolist()})
2 predictions
/opt/conda/lib/python3.7/site-packages/pandas/core/generic.py in __getattr__(self, name)
5137 if self._info_axis._can_hold_identifiers_and_holds_name(name):
5138 return self[name]
-> 5139 return object.__getattribute__(self, name)
5140
5141 def __setattr__(self, name: str, value) -> None:
AttributeError: 'DataFrame' object has no attribute 'Survived'Honestly, I have no idea wtf any of this means. I have tried googling this issue and have come up with nothing.
Any help would be greatly appreciated. I know it's a lot.
Double check if there's a space in the column name. 'Survived ' vs 'Survived' It happens more often than you'd think especially with CSV data source.
It's an issue with how you're calling the data and if it's actually there.
train.loc[:,['Survived','Sex']]
tells me that there's a DataFrame (which is from pandas, hence the error) called train and this line is trying to access parts of that dataframe (it's just a type of an array). Specifically, it's trying to access columns named Survived and Sex.
Similarly, this line tells me there's another dataframe (df) known as test with a column named Sex and this is access that data.
test.loc[:,['Sex']]The error code also informs me of some things
predictions = pandas.DataFrame({'PassengerId': test.PassengerId,'Survived': hypothesis.Survived.tolist()})
There's another df called predictions that's of dict type which is trying to access information from the another hypothesis df. The attribute it's tryin to access in the second key of the dict is
hypothesis.Survived.tolist()
which is a way of calling a column from that df. That is, when the predictions line is executed, it's trying to pull all the values from the Survived column of the hypothesis df.
The error is that the df doesn't actually have a column named Survived. So either there's missing data, or you're calling it wrong, or there's a missing reference.
Without knowing more about your code and your question, I can't really extrapolate much more.