According to the documentation and the comments in the sqlalchemy.Column class, we should use the class sqlalchemy.schema.Index to specify an index that contains multiple columns.
However, the example shows how to do it by directly using the Table object like this:
meta = MetaData()
mytable = Table(‘mytable’, meta,
# an indexed column, with in….
This question already has answers here:
How do I convert a Pandas series or index to a NumPy array? [duplicate]
(8 answers)
Closed 3 years ago.
I’m probably using poor search terms when trying to find this answer. Right now,….
I have a dataframe like this one:
In [10]: df
Out[10]:
Column 1
foo
Apples 1
Oranges 2
Puppies 3
Ducks 4
How to remove index name foo from that dataframe?
The desired output is like this:
In [10]: df
Out[10]:
Column 1
Apples 1
Oranges 2
Puppies ….
I have DataFrame with column Sales.
How can I split it into 2 based on Sales value?
First DataFrame will have data with ‘Sales’ < s and second with 'Sales' >= s
….
I have a Dictionary below:
colors = {
“blue” : “5”,
“red” : “6”,
“yellow” : “8”,
}
How do I index the first entry in the dictionary?
colors[0] will return a KeyError for obvious reasons.
….
I’m simply trying to access named pandas columns by an integer.
You can select a row by location using df.ix[3].
But how to select a column by integer?
My dataframe:
df=pandas.DataFrame({‘a’:np.random.rand(5), ‘b’:np.random.rand(5)})
….
I have the following Python list (can also be a tuple):
myList = [‘foo’, ‘bar’, ‘baz’, ‘quux’]
I can say
>>> myList[0:3]
[‘foo’, ‘bar’, ‘baz’]
>>> myList[::2]
[‘foo’, ‘baz’]
>>> myList[1::2]
[‘bar’, ‘quux’]
How do I explicitly pick out items whose indices have no specific patterns? For example, I want to select [0,2,3]. Or from a very big list o….
Say I have the following dataframe:
What is the most efficient way to update the values of the columns feat and another_feat where the stream is number 2?
Is this it?
for index, row in df.iterrows():
if df1.loc[index,’stream’] == 2:
# do something
UPDATE:
What to do if I have more than a 100 columns? I don’t want to explicitly name th….
As we all know, the pythonic way to swap the values of two items a and b is
a, b = b, a
and it should be equivalent to
b, a = a, b
However, today when I was working on some code, I accidentally found that the following two swaps give different results:
nums = [1, 2, 4, 3]
i = 2
nums[i], nums[nums[i]-1] = nums[nums[i]-1], nums[i]
print(nums)
# [1….
I’m confused about the rules Pandas uses when deciding that a selection from a dataframe is a copy of the original dataframe, or a view on the original.
If I have, for example,
df = pd.DataFrame(np.random.randn(8,8), columns=list(‘ABCDEFGH’), index=range(1,9))
I understand that a query returns a copy so that something like
foo = df.query(‘2 < ind....