unable to get the index based on conditions

user_15130457 0
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I tried to get the index of node_id column with specific value but my code doesn't return anything but return the index of option column. I can not tell the reason why there is the diffs between two columns. Could any one give me tips ?? Thank you so much.

client_data = """node_id,option,before_id
    1,A,
    5,A,4
    3,B,2
    4,C,1
    8,C,2
    6,A,
    2,A,1
    7,C,6
    """

    df = pd.read_csv(io.StringIO(client_data), dtype='string', error_bad_lines=False)
    before_ind = df.loc[df['node_id'] == 1].index
    print(before_ind)

output of before_ind = df.loc[df['node_id'] == 1].index

Int64Index([], dtype='int64')

If I do before_ind = df.loc[df['option'] == 'C'].index

  node_id option before_id
3       4      C         1
4       8      C         2
7       7      C         6
pandas python-3.x
2 Answers

The values of 'node id' is string so use:

before_ind = df.loc[df['node_id'] == '1'].index

you can cross verify by this by using .dtypes attribute:

print(df.dtypes)

#output:
node_id      string
option       string
before_id    string
dtype: object

OR

typecase 'node_id' to int by using astype() method:

df['nodr id']=df['node id'].astype(int) 
#then use:
before_ind = df.loc[df['node_id'] == 1].index

OR

Don't use dtype parameter in read_csv() method and let pandas to manupulate dtypes:

df = pd.read_csv(io.StringIO(client_data), error_bad_lines=False)
user_142898920

It's because you do it from a StringIO, which makes it a string.

Try converting it to a integer:

df['node id'] = df['node id'].astype(int)
print(df.loc[df['node_id'] == 1].index)

Or keep it as a string:

print(df.loc[df['node_id'] == "1"].index)
user_87083640
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