How to filter Excel column? - path

Question

I am looking for a solution in python for my data which is in an excel file that contains different statements and numbers. I want to filter out the rows on the base of column values.
import pandas as pd
df=pd.read.excel("Data.xlsx")
df[df.Numbers.apply(lambda x: str(x).isdigit())]
df.to_excel("Data1.xlsx")
Any suggestions please?

Answer 1

Here is one way to perform the filtering, using pandas' string tools and boolean masks. I did each step separately (easier to test, and easier to understand in the future).
# remove CAS and Cascade
mask = (df['Evaluations'].str.startswith('CAS') |
df['Evaluations'].str.contains('CASCADE'))
df = df[~mask]
# remove Numbers starting with 21 or 99
mask = (df['Numbers'].astype(str).str.startswith('21') |
df['Numbers'].astype(str).str.startswith('99'))
df = df[~mask]
# remove letter as 2th character (1 => zero-based indexing)
mask = df['Numbers'].astype(str).apply(lambda x: x[1].isalpha())
df = df[~mask]
# write to file
with open('Data1.xlsx', 'wb') as handle:
df.to_excel(handle)
print(df)
Evaluations Numbers
2 Nastolgic behaviours of people 75903324
3 google drive 76308764
6 Tesla's new inventions 83492836
7 Electric cars 78363522

Answer 2

1- If in the column named Evaluations, its content starts with "OBS" or has the word "Obsolete" in it then remove these rows
(^OBS|Obsolete)
2- If the column value in the Numbers column start with digits "99" or "51" then remove these rows
^(99|51)
3- If the 5th digit in the Numbers column is an alphabetic character then also remove these rows
^\d{4}\w
These are the Regexes that will help match these conditions.