52
votes
8
answers
1K
views
dropping infinite values from dataframes in pandas?
what is the quickest/simplest way to drop nan and inf/-inf values from a pandas DataFrame without resetting mo
53
votes
10
answers
638
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How to take column-slices of dataframe in pandas
I load some machine learning data from a CSV file. The first 2 columns are observations and the remaining colu
62
votes
23
answers
2.8K
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What does axis in pandas mean?
Here is my code to generate a dataframe: import pandas as pd import numpy as np dff = pd.DataFrame(np.random
60
votes
9
answers
1.3K
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Creating a Pandas DataFrame from a Numpy array: How do I specify the index column and column headers?
I have a Numpy array consisting of a list of lists, representing a two-dimensional array with row labels and c
53
votes
13
answers
2.3K
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Converting between datetime, Timestamp and datetime64
How do I convert a numpy.datetime64 object to a datetime.datetime (or Timestamp)? In the following code, I cr
53
votes
10
answers
2.5K
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Pandas conditional creation of a series/dataframe column
I have a dataframe along the lines of the below: Type Set 1 A Z 2 B Z
60
votes
10
answers
1.8K
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Pandas read_csv low_memory and dtype options
When calling df = pd.read_csv('somefile.csv') I get: /Users/josh/anaconda/envs/py27/lib/pytho
59
votes
7
answers
2.9K
views
pandas create new column based on values from other columns / apply a function of multiple columns, row-wise
I want to apply my custom function (it uses an if-else ladder) to these six columns (ERI_Hispanic, ERI_AmerInd
62
votes
15
answers
744
views
Convert pandas dataframe to NumPy array
I am interested in knowing how to convert a pandas dataframe into a NumPy array. dataframe: import numpy as
53
votes
11
answers
1.3K
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How do I select rows from a DataFrame based on column values?
How can I select rows from a DataFrame based on values in some column in Pandas? In SQL, I would use: SELECT *
54
votes
29
answers
2.8K
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How to iterate over rows in a DataFrame in Pandas
I have a DataFrame from Pandas: import pandas as pd inp = [{'c1':10, 'c2':100}, {'c1
57
votes
16
answers
368
views
"Large data" workflows using pandas
I have tried to puzzle out an answer to this question for many months while learning pandas. I use SAS for my
