create dataframe from columns of another dataframe

Question

I have dataframe df which contains a column check_r2 which contains values either True or False. I want to create another dataframe df1 which will contain rows for only those which have check_r2 as True

I tried with this code but getting empty dataframe as output, I am creating this dataframe from excel, where column values are in capital i.e TRUE or FALSE but when I Print them using print(df) I get True or False as output, I tried both ways while comparing but the output was same

code
df = read_data()
df1 = pd.DataFrame()
df1 = df[df['check_r2'] =="True"]

also tried

df1 = df1.append(df[df['check_r2'] =="True"])

Can you add the actual excel values?

sotmot
– sotmot

2021-01-02 13:38:33 +00:00
Commented Jan 2, 2021 at 13:38 — sotmot
– sotmot, Commented Jan 2, 2021 at 13:38

Epsi95 · Accepted Answer · 2021-01-02 13:45:44Z

1

df1 = df[df['check_r2'] ==True]

check the datatype

df.info()

check_r2    9 non-null bool

Pandas is converting it to boolean.

edited Jan 2, 2021 at 13:45

answered Jan 2, 2021 at 13:44

Epsi95

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3 Comments

user4599 Over a year ago

this worked, but arent the values suppposed to be string

user4599 Over a year ago

Pandas is converting it to boolean.>>>> yes, will keep this in mind, thank you.

Epsi95 Over a year ago

Actually, when you are storing TRUE & FALSE in excel, it is stored as a logical value. Check by =TYPE(cell number), it will return 4 which shows it is a logical value. Excel stores additional value, unlike CSV. If you want to stop pandas from interpreting on their own you can use df = pandas.read_excel("temp.xlsx", dtype={"check_r2":object}) but, in this case it will not help because pandas will use excel own implementation which is also boolean. Try saving it to CSV and using df = pandas.read_csv("temp.xlsx", dtype={"check_r2":object}), then you will see TRUE, False.

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