import pandas as pd

# get the string which represent integer
s1 = pd.Series(['$' , '11' , 'a1', '123'])
print(f'\ns1\n{s1}')
filt : pd.Series = s1.apply(lambda string : string.isnumeric())
print(f'\nis numeric in series using filt: {filt}')

# get the numeric based on res
res_series = s1[filt]
print(f'\nres_series : {res_series}')
print(f'\nres_series.array : {res_series.array}')
print(f'\ntype(res_series) : {type(res_series)}')

e8317f94a21798f89d268772627710e306118b51
<mask token>

<mask token>
print(f'\ns1\n{s1}')
filt: pd.Series = s1.apply(lambda string: string.isnumeric())
print(f"""
is numeric in series using filt: {filt}""")
<mask token>
print(f"""
res_series : {res_series}""")
print(f"""
res_series.array : {res_series.array}""")
print(f"""
type(res_series) : {type(res_series)}""")

<mask token>
s1 = pd.Series(['$', '11', 'a1', '123'])
print(f'\ns1\n{s1}')
filt: pd.Series = s1.apply(lambda string: string.isnumeric())
print(f"""
is numeric in series using filt: {filt}""")
res_series = s1[filt]
print(f"""
res_series : {res_series}""")
print(f"""
res_series.array : {res_series.array}""")
print(f"""
type(res_series) : {type(res_series)}""")

import pandas as pd
s1 = pd.Series(['$', '11', 'a1', '123'])
print(f'\ns1\n{s1}')
filt: pd.Series = s1.apply(lambda string: string.isnumeric())
print(f"""
is numeric in series using filt: {filt}""")
res_series = s1[filt]
print(f"""
res_series : {res_series}""")
print(f"""
res_series.array : {res_series.array}""")
print(f"""
type(res_series) : {type(res_series)}""")

import pandas as pd

# get the string which represent integer
s1 = pd.Series(['$' , '11' , 'a1', '123'])
print(f'\ns1\n{s1}')
filt : pd.Series = s1.apply(lambda string : string.isnumeric())
print(f'\nis numeric in series using filt: {filt}')

# get the numeric based on res
res_series = s1[filt]
print(f'\nres_series : {res_series}')
print(f'\nres_series.array : {res_series.array}')
print(f'\ntype(res_series) : {type(res_series)}')
