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Balapradeepck
commented
Oct 29, 2018
Balapradeepck
commented
- Import file from specific location
- Remove any alphabet characters or special characters except numbers (0 – 9) at any place in any column.
- Converts values to float.
- Replace any missing values to average of that column
1. Import file from specific location 2. Remove any alphabet characters or special characters except numbers (0 – 9) at any place in any column. 3. Converts values to float. 4. Replace any missing values to average of that column
Harishac
reviewed
Nov 3, 2018
| import pandas as pd | ||
| import numpy as np | ||
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| df_raw=pd.read_csv('Source/test1.csv') |
Owner
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Cannot take a Hardcoded location.
It has to be pd.read_csv(location)
Harishac
reviewed
Nov 3, 2018
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| df_raw=pd.read_csv('Source/test1.csv') | ||
| df1=df_raw.replace('[^0-9]','',regex=True).astype(float) | ||
| df2=df1.fillna(df1.mean()) |
Owner
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pre process function takes two arguments(location , method)
Use "method" to determine the type of cleaning.
ex:
If method == "Drop":
Do dropna()
elif method == "Prev":
Use replace null by previous value.
elif method == "avg":
add avg
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