Can't replace string symbol “-” in dataframe on jupyter notebook

I import data from "url = ("http://finviz.com/quote.ashx?t=" + symbol.lower())"

and got the table:

        P/B    P/E Forward P/E   PEG Debt/Eq EPS (ttm) Dividend %     ROE  

AMZN  18.73  92.45       56.23  2.09    1.21     16.25          -  26.70%   

GOOG   4.24  38.86           -  2.55       -     26.65          -       -   

PG     4.47  22.67       19.47  3.45    0.61      4.05      3.12%  18.80%   

KO    11.04  30.26       21.36  4.50    2.45      1.57      3.29%  15.10%   

IBM    5.24   9.28        8.17  9.67    2.37     12.25      5.52%  30.90%   



         ROI   EPS Q/Q Insider Own  

AMZN   3.50%  1026.20%      16.20%  

GOOG       -    36.50%       5.74%  

PG    13.10%    15.50%       0.10%  

KO    12.50%    56.80%       0.10%  

IBM   17.40%     0.70%       0.10%

Then I was trying to convert string to float:

df = df[(df['P/E'].astype(float)<20) & (df['P/B'].astype(float) < 3)]

and got "ValueError: could not convert string to float:"

I think that values 0.70% and sign "-" is the problem.

I tried:

df.replace("-","0")

df.replace('-', 0)

df.replace('-', nan)

But nothing works.

edited Jan 2 at 0:18

Wen-Ben

114k83368

asked Jan 1 at 23:24

basta burburlajev

Minus sign is not a problem for casting to float. But % is.

– SpghttCd
Jan 1 at 23:31

add a comment |

I import data from "url = ("http://finviz.com/quote.ashx?t=" + symbol.lower())"

and got the table:

        P/B    P/E Forward P/E   PEG Debt/Eq EPS (ttm) Dividend %     ROE  

AMZN  18.73  92.45       56.23  2.09    1.21     16.25          -  26.70%   

GOOG   4.24  38.86           -  2.55       -     26.65          -       -   

PG     4.47  22.67       19.47  3.45    0.61      4.05      3.12%  18.80%   

KO    11.04  30.26       21.36  4.50    2.45      1.57      3.29%  15.10%   

IBM    5.24   9.28        8.17  9.67    2.37     12.25      5.52%  30.90%   



         ROI   EPS Q/Q Insider Own  

AMZN   3.50%  1026.20%      16.20%  

GOOG       -    36.50%       5.74%  

PG    13.10%    15.50%       0.10%  

KO    12.50%    56.80%       0.10%  

IBM   17.40%     0.70%       0.10%

Then I was trying to convert string to float:

df = df[(df['P/E'].astype(float)<20) & (df['P/B'].astype(float) < 3)]

and got "ValueError: could not convert string to float:"

I think that values 0.70% and sign "-" is the problem.

I tried:

df.replace("-","0")

df.replace('-', 0)

df.replace('-', nan)

But nothing works.

edited Jan 2 at 0:18

Wen-Ben

114k83368

asked Jan 1 at 23:24

basta burburlajev

Minus sign is not a problem for casting to float. But % is.

– SpghttCd
Jan 1 at 23:31

add a comment |

I import data from "url = ("http://finviz.com/quote.ashx?t=" + symbol.lower())"

and got the table:

        P/B    P/E Forward P/E   PEG Debt/Eq EPS (ttm) Dividend %     ROE  

AMZN  18.73  92.45       56.23  2.09    1.21     16.25          -  26.70%   

GOOG   4.24  38.86           -  2.55       -     26.65          -       -   

PG     4.47  22.67       19.47  3.45    0.61      4.05      3.12%  18.80%   

KO    11.04  30.26       21.36  4.50    2.45      1.57      3.29%  15.10%   

IBM    5.24   9.28        8.17  9.67    2.37     12.25      5.52%  30.90%   



         ROI   EPS Q/Q Insider Own  

AMZN   3.50%  1026.20%      16.20%  

GOOG       -    36.50%       5.74%  

PG    13.10%    15.50%       0.10%  

KO    12.50%    56.80%       0.10%  

IBM   17.40%     0.70%       0.10%

Then I was trying to convert string to float:

df = df[(df['P/E'].astype(float)<20) & (df['P/B'].astype(float) < 3)]

and got "ValueError: could not convert string to float:"

I think that values 0.70% and sign "-" is the problem.

I tried:

df.replace("-","0")

df.replace('-', 0)

df.replace('-', nan)

But nothing works.

edited Jan 2 at 0:18

Wen-Ben

114k83368

asked Jan 1 at 23:24

basta burburlajev

I import data from "url = ("http://finviz.com/quote.ashx?t=" + symbol.lower())"

and got the table:

        P/B    P/E Forward P/E   PEG Debt/Eq EPS (ttm) Dividend %     ROE  

AMZN  18.73  92.45       56.23  2.09    1.21     16.25          -  26.70%   

GOOG   4.24  38.86           -  2.55       -     26.65          -       -   

PG     4.47  22.67       19.47  3.45    0.61      4.05      3.12%  18.80%   

KO    11.04  30.26       21.36  4.50    2.45      1.57      3.29%  15.10%   

IBM    5.24   9.28        8.17  9.67    2.37     12.25      5.52%  30.90%   



         ROI   EPS Q/Q Insider Own  

AMZN   3.50%  1026.20%      16.20%  

GOOG       -    36.50%       5.74%  

PG    13.10%    15.50%       0.10%  

KO    12.50%    56.80%       0.10%  

IBM   17.40%     0.70%       0.10%

Then I was trying to convert string to float:

df = df[(df['P/E'].astype(float)<20) & (df['P/B'].astype(float) < 3)]

and got "ValueError: could not convert string to float:"

I think that values 0.70% and sign "-" is the problem.

I tried:

df.replace("-","0")

df.replace('-', 0)

df.replace('-', nan)

But nothing works.

python pandas replace

edited Jan 2 at 0:18

Wen-Ben

114k83368

asked Jan 1 at 23:24

basta burburlajev

edited Jan 2 at 0:18

Wen-Ben

114k83368

asked Jan 1 at 23:24

basta burburlajev

edited Jan 2 at 0:18

Wen-Ben

114k83368

edited Jan 2 at 0:18

Wen-Ben

114k83368

edited Jan 2 at 0:18

Wen-Ben

114k83368

asked Jan 1 at 23:24

basta burburlajev

asked Jan 1 at 23:24

basta burburlajev

asked Jan 1 at 23:24

basta burburlajev

Minus sign is not a problem for casting to float. But % is.

– SpghttCd
Jan 1 at 23:31

add a comment |

Minus sign is not a problem for casting to float. But % is.

– SpghttCd
Jan 1 at 23:31

Minus sign is not a problem for casting to float. But % is.

– SpghttCd
Jan 1 at 23:31

add a comment |

2 Answers
2

active

oldest

votes

You may need to assign it back

df=df.replace("-","0")

And I recommend to_numeric

df['P/E']=pd.to_numeric(df['P/E'],errors = 'coerce')

df['P/B']=pd.to_numeric(df['P/B'],errors = 'coerce')

edited Jan 2 at 0:28

answered Jan 2 at 0:19

Wen-Ben

114k83368

Thank you it works fine

– basta burburlajev
Jan 2 at 11:38

add a comment |

You should use numpy:

import numpy as np

then the next replacement:

df = df.replace('-', np.nan)

Next, change the datatype:

df = df['Forward P/E'].astype(float)

Lastly, you can test if the datatype is float64.

answered Jan 2 at 15:05

Antonio Andrés

1039

Thank you Andres, it works.

– basta burburlajev
Jan 3 at 23:07

add a comment |

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2 Answers
2

active

oldest

votes

2 Answers
2

active

oldest

votes

You may need to assign it back

df=df.replace("-","0")

And I recommend to_numeric

df['P/E']=pd.to_numeric(df['P/E'],errors = 'coerce')

df['P/B']=pd.to_numeric(df['P/B'],errors = 'coerce')

edited Jan 2 at 0:28

answered Jan 2 at 0:19

Wen-Ben

114k83368

Thank you it works fine

– basta burburlajev
Jan 2 at 11:38

add a comment |

You may need to assign it back

df=df.replace("-","0")

And I recommend to_numeric

df['P/E']=pd.to_numeric(df['P/E'],errors = 'coerce')

df['P/B']=pd.to_numeric(df['P/B'],errors = 'coerce')

edited Jan 2 at 0:28

answered Jan 2 at 0:19

Wen-Ben

114k83368

Thank you it works fine

– basta burburlajev
Jan 2 at 11:38

add a comment |

You may need to assign it back

df=df.replace("-","0")

And I recommend to_numeric

df['P/E']=pd.to_numeric(df['P/E'],errors = 'coerce')

df['P/B']=pd.to_numeric(df['P/B'],errors = 'coerce')

edited Jan 2 at 0:28

answered Jan 2 at 0:19

Wen-Ben

114k83368

You may need to assign it back

df=df.replace("-","0")

And I recommend to_numeric

df['P/E']=pd.to_numeric(df['P/E'],errors = 'coerce')

df['P/B']=pd.to_numeric(df['P/B'],errors = 'coerce')

edited Jan 2 at 0:28

answered Jan 2 at 0:19

Wen-Ben

114k83368

edited Jan 2 at 0:28

answered Jan 2 at 0:19

Wen-Ben

114k83368

answered Jan 2 at 0:19

Wen-Ben

114k83368

answered Jan 2 at 0:19

Wen-Ben

114k83368

Thank you it works fine

– basta burburlajev
Jan 2 at 11:38

add a comment |

Thank you it works fine

– basta burburlajev
Jan 2 at 11:38

Thank you it works fine

– basta burburlajev
Jan 2 at 11:38

add a comment |

You should use numpy:

import numpy as np

then the next replacement:

df = df.replace('-', np.nan)

Next, change the datatype:

df = df['Forward P/E'].astype(float)

Lastly, you can test if the datatype is float64.

answered Jan 2 at 15:05

Antonio Andrés

1039

Thank you Andres, it works.

– basta burburlajev
Jan 3 at 23:07

add a comment |

You should use numpy:

import numpy as np

then the next replacement:

df = df.replace('-', np.nan)

Next, change the datatype:

df = df['Forward P/E'].astype(float)

Lastly, you can test if the datatype is float64.

answered Jan 2 at 15:05

Antonio Andrés

1039

Thank you Andres, it works.

– basta burburlajev
Jan 3 at 23:07

add a comment |

You should use numpy:

import numpy as np

then the next replacement:

df = df.replace('-', np.nan)

Next, change the datatype:

df = df['Forward P/E'].astype(float)

Lastly, you can test if the datatype is float64.

answered Jan 2 at 15:05

Antonio Andrés

1039

You should use numpy:

import numpy as np

then the next replacement:

df = df.replace('-', np.nan)

Next, change the datatype:

df = df['Forward P/E'].astype(float)

Lastly, you can test if the datatype is float64.

answered Jan 2 at 15:05

Antonio Andrés

1039

answered Jan 2 at 15:05

Antonio Andrés

1039

answered Jan 2 at 15:05

Antonio Andrés

1039

answered Jan 2 at 15:05

Antonio Andrés

1039

Thank you Andres, it works.

– basta burburlajev
Jan 3 at 23:07

add a comment |

Thank you Andres, it works.

– basta burburlajev
Jan 3 at 23:07

Thank you Andres, it works.

– basta burburlajev
Jan 3 at 23:07

add a comment |

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