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Python populating dataframe in pandas from text files


Python populating dataframe in pandas from text files

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Python populating dataframe in pandas from text files
Tag : python , By : Ansari
Date : January 11 2021, 03:34 PM

I wish this helpful for you Use custom function with Series.apply and read files in pure python (faster like pandas):
import ast

def f(x):
    out = []
    path = 'files/'
    #if necessary convert string repr of lists to lists
    x = ast.literal_eval(x)
    for file in x:
        with open('{}{}.txt'.format(path, file)) as f:
            c = ' '.join(f.readlines())
            out.append(c)
    return ' '.join(out)


df['content'] = df['Files'].apply(f)
print (df)
   ID          Files              content
0   1   [12, 15, 19]        I like pandas
1   2  [15, 18, 103]  like something else

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Populating a Pandas DataFrame frome another DataFrame based on column names


Tag : python , By : Andrew
Date : March 29 2020, 07:55 AM
To fix this issue I have a DataFrame of the following form: , You can just use the list to select them:
In [44]:

cols = ['a', 'b', 'b', 'a', 'c']
df[cols]
Out[44]:
   a  b  b  a  c
0  1  4  4  1  6
1  3  2  2  3  4
2  4  1  1  4  5

[3 rows x 5 columns]

Populating pandas dataframe using conditional group from another dataframe


Tag : python , By : D B
Date : March 29 2020, 07:55 AM
This might help you I found one solution, perhaps not very elegant, and I'll check back in case anyone actually sees this and has a better one. I created a list of the column headers, then used iterrows to iterate through both each column and row in the column:
    batcol = pd.DataFrame(df1.columns)
    batcol = batcol.iloc[6:-1]
    batcol = batcol.reset_index(drop=True)
    for index, row in batcol.iterrows():
        for i, rows in df2.iterrows():
            df2.loc[i, row] = df1[((df1['date'] < rows['date']) & (df1['team'] == rows['opp'])) == True].mean()[row].sum()

Python Pandas - Initialising and Populating a DataFrame


Tag : python , By : SachinJadhav
Date : March 29 2020, 07:55 AM
To fix this issue df = pd.DataFrame() produces an empty dataframe... But it's more empty than other empty dataframes. It has no index and no columns.
df['First'] = 68 assigns the value of 68 to a column named 'First' for every index value. You'll note that the columns ['First', 'Second'] now exist. There were simply no index values for which to make the assignments of 68 and 157
df = pd.DataFrame(index=[1, 2, 3])
df['First'] = 68
df['Second'] = 157

print(df)

   First  Second
1     68     157
2     68     157
3     68     157

Populating a Pandas dataframe where index and column are values of another dataframe


Tag : pandas , By : user87752
Date : March 29 2020, 07:55 AM
hope this fix your issue I have a dataframe with columns ['ID', 'DATE', 'VALUE']. The way that the data I am sourcing comes in, I have many duplicate IDs, each of which has a duplicate price--so, for instance, the frame will come in with , We using combine_first+pivot_table
newdf.combine_first(pd.pivot_table(df,index='Date',columns='ID',values='Value',aggfunc='sum'))
Out[442]: 
          a     b
1/1/17  2.0   5.0
1/2/17  3.0  13.0
1/3/17  4.0   NaN

Python:Pandas Find the availability of a text inside a Pandas (Dataframe)


Tag : python , By : redha
Date : March 29 2020, 07:55 AM
Hope that helps I am having two columns ColA ColB in pandas dataframe, I want to compare ColB with ColA if colA contains matching word with colB then i have to update colC as available. , Try the following:
import pandas as pd

# Initialize example dataframe
data = [
    ["You can extract_insights on product reception", "insights"],
    ["user various sources like extract_insights etc.", "insights"],
    ["some other sourced mail by using signals from state art", "text"],
]
df = pd.DataFrame(data=data, columns=["ColA", "ColB"])

# Create column C with comparison results
df["ColC"] = [
    "AVB" if (b in a) else "NAVB"
    for (a, b) in zip(df["ColA"], df["ColB"])
]

print(df)
# Output:
#                                                 ColA      ColB  ColC
# 0      You can extract_insights on product reception  insights   AVB
# 1    user various sources like extract_insights etc.  insights   AVB
# 2  some other sourced mail by using signals from ...      text  NAVB
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