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Having trouble reading Pandas dataframe with SciLearn Kit

By : Hari ram
Date : October 17 2020, 08:10 PM
fixed the issue. Will look into that further As mentioned by @Jarad, You have to feed a list or series to tfidf_vectorizer. Hence, the fix to your issues is
code :
tfidf = tfidf_vectorizer.fit_transform(subset_data[records])

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Trouble plotting pandas DataFrame

By : user2846103
Date : March 29 2020, 07:55 AM
I hope this helps you . You should first convert the strings in the date column, to actual datetime values:
code :
df['date'] = pd.to_datetime(df['date'])
df = df.set_index('date')
df.plot(x='date', y='y')

Reading values from Pandas dataframe rows into equations and entering result back into dataframe

By : hilding
Date : March 29 2020, 07:55 AM
it should still fix some issue I have a dataframe. For each row of the dataframe: I need to read values from two column indexes, pass these values to a set of equations, enter the result of each equation into its own column index in the same row, go to the next row and repeat.
code :
# If your equations are simple enough, do operations column-wise in Pandas:

import pandas as pd

test = pd.DataFrame([[1,2],[3,4],[5,6]])
test # Default column names are 0, 1
test[0] # This is column 0 
test.icol(0) # This is COLUMN 0-indexed, returned as a Series 
test.columns=(['S','Q']) # Column names are easier to use
test #Column names! Use them column-wise:
test['result'] = test.S**2 + test.Q
test # results stored in DataFrame

# For more complicated stuff, try apply, as in Python pandas apply on more columns :

def toyfun(df):
    return df[0]-df[1]**2

test['out2']=test[['S','Q']].apply(toyfun, axis=1)

# You can also define the column names when you generate the DataFrame:
test2 = pd.DataFrame([[1,2],[3,4],[5,6]],columns = (list('AB')))

Trouble reading CSV data into Pandas dataframe (Python/Pandas)

By : user3592890
Date : March 29 2020, 07:55 AM
To fix this issue One solution is to pass the skipinitialspace argument, to specify that all whitespace after the delimiter should be ignored:
code :
pd.read_csv('filename.txt', sep=",", header=1, na_values=["-999"], skipinitialspace=True)

pandas: trouble transforming dataframe into aggregated dataframe

By : npr-dal
Date : March 29 2020, 07:55 AM
around this issue I'd perform a groupby on the 'DATE' and 'GROUP' columns, then call transform on 'STATUS' column and call value_counts / count, transform will return a series aligned to your orig df, so it allows you to add it back as a new column:
code :
In [64]:

df['PCT'] = df.groupby(['DATE','GROUP'])['STATUS'].transform(lambda x: x.value_counts() / x.count())
         DATE GROUP  X  Y STATUS        PCT
0  2014-01-01     A  0  0   PASS  0.6666667
1  2014-01-01     A  0  1   FAIL  0.3333333
2  2014-01-01     A  1  0   PASS  0.6666667
3  2014-01-02     B  0  0   PASS  0.6666667
4  2014-01-02     B  0  1   PASS  0.3333333
5  2014-01-02     B  1  1   FAIL  0.6666667

Pandas - Reading multiple excel files into a single pandas Dataframe

By : user3487567
Date : March 29 2020, 07:55 AM
wish of those help Rather than create the pd.DataFrame based on the list, use pd.concat to concatenate them, i.e.
code :
file = pd.concat(list_)
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