Add column based on different conditions for different columns

Add column based on different conditions for different columns | python pandas

I have a dataframe with 4 columns:

c1        c2        c3      GName

0.221445  0.300534  5.689   KDD

0.001000  0.969000  15.140  ACC

1.000000  0.094000  -0.245  QETF

And dataframe called file of one column:

GName

Abd

kkoew

KDD

pwqh

ACC

dsewf

I need to add new column call label that based on checking the scores in c1, c2 and c3 and GName

So, if the majority of the 3 scores agreed on their conditions (2 out of the 3 or all the 3) and the value of GName exist in the dataframe file; the label = 1, otherwise the label = 0

The conditions of c1 should be > 0.95

c2 should be > 0.50

c3 should be > 15

The output will be like this:

c1        c2        c3      GName label

0.221445  0.300534  5.689   KDD   0  (because 0 out of 3 and KDD in file)

0.001000  0.969000  15.140  ACC   1  (because 2 out of 3 and ACC in file)

1.000000  0.94060  -0.245  QETF   0  (because 2 out of 3 but QETF not in file)

I'm struggling with those different conditions, any help please?

asked Nov 20 at 23:45

Sara Wasl

817

add a comment |

I have a dataframe with 4 columns:

c1        c2        c3      GName

0.221445  0.300534  5.689   KDD

0.001000  0.969000  15.140  ACC

1.000000  0.094000  -0.245  QETF

And dataframe called file of one column:

GName

Abd

kkoew

KDD

pwqh

ACC

dsewf

I need to add new column call label that based on checking the scores in c1, c2 and c3 and GName

So, if the majority of the 3 scores agreed on their conditions (2 out of the 3 or all the 3) and the value of GName exist in the dataframe file; the label = 1, otherwise the label = 0

The conditions of c1 should be > 0.95

c2 should be > 0.50

c3 should be > 15

The output will be like this:

c1        c2        c3      GName label

0.221445  0.300534  5.689   KDD   0  (because 0 out of 3 and KDD in file)

0.001000  0.969000  15.140  ACC   1  (because 2 out of 3 and ACC in file)

1.000000  0.94060  -0.245  QETF   0  (because 2 out of 3 but QETF not in file)

I'm struggling with those different conditions, any help please?

asked Nov 20 at 23:45

Sara Wasl

817

add a comment |

I have a dataframe with 4 columns:

c1        c2        c3      GName

0.221445  0.300534  5.689   KDD

0.001000  0.969000  15.140  ACC

1.000000  0.094000  -0.245  QETF

And dataframe called file of one column:

GName

Abd

kkoew

KDD

pwqh

ACC

dsewf

I need to add new column call label that based on checking the scores in c1, c2 and c3 and GName

So, if the majority of the 3 scores agreed on their conditions (2 out of the 3 or all the 3) and the value of GName exist in the dataframe file; the label = 1, otherwise the label = 0

The conditions of c1 should be > 0.95

c2 should be > 0.50

c3 should be > 15

The output will be like this:

c1        c2        c3      GName label

0.221445  0.300534  5.689   KDD   0  (because 0 out of 3 and KDD in file)

0.001000  0.969000  15.140  ACC   1  (because 2 out of 3 and ACC in file)

1.000000  0.94060  -0.245  QETF   0  (because 2 out of 3 but QETF not in file)

I'm struggling with those different conditions, any help please?

asked Nov 20 at 23:45

Sara Wasl

817

I have a dataframe with 4 columns:

c1        c2        c3      GName

0.221445  0.300534  5.689   KDD

0.001000  0.969000  15.140  ACC

1.000000  0.094000  -0.245  QETF

And dataframe called file of one column:

GName

Abd

kkoew

KDD

pwqh

ACC

dsewf

I need to add new column call label that based on checking the scores in c1, c2 and c3 and GName

So, if the majority of the 3 scores agreed on their conditions (2 out of the 3 or all the 3) and the value of GName exist in the dataframe file; the label = 1, otherwise the label = 0

The conditions of c1 should be > 0.95

c2 should be > 0.50

c3 should be > 15

The output will be like this:

c1        c2        c3      GName label

0.221445  0.300534  5.689   KDD   0  (because 0 out of 3 and KDD in file)

0.001000  0.969000  15.140  ACC   1  (because 2 out of 3 and ACC in file)

1.000000  0.94060  -0.245  QETF   0  (because 2 out of 3 but QETF not in file)

I'm struggling with those different conditions, any help please?

python pandas dataframe

asked Nov 20 at 23:45

Sara Wasl

817

asked Nov 20 at 23:45

Sara Wasl

817

asked Nov 20 at 23:45

Sara Wasl

817

asked Nov 20 at 23:45

Sara Wasl

817

asked Nov 20 at 23:45

Sara Wasl

817

add a comment |

1 Answer
1

active

oldest

votes

The way I would do it is this:

import pandas as pd



df = pd.DataFrame({'c1':[0.221445, 0.001000, 1.000000],

                   'c2':[0.300534, 0.969000, 0.094000],

                   'c3':[5.689, 15.140, -0.245],

                   'GName':['KDD', 'ACC', 'QETF']})

file = pd.DataFrame({'GName':['KDD', 'ACC']})



conditions = (df['c1'] > 0.95).astype(int) + (df['c2'] > 0.5).astype(int) + (df['c3'] > 15).astype(int)

conditions = (conditions >= 2) & (df['GName'].isin(file['GName']))

df['label'] = 0

df.loc[conditions, 'label'] = 1



>>> df

         c1        c2      c3 GName  label

0  0.221445  0.300534   5.689   KDD      0

1  0.001000  0.969000  15.140   ACC      1

2  1.000000  0.094000  -0.245  QETF      0

It would be nice if you could include code to generate your dataframe in your question, as well.

answered Nov 21 at 0:12

CJ59

1,2171214

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

The way I would do it is this:

import pandas as pd



df = pd.DataFrame({'c1':[0.221445, 0.001000, 1.000000],

                   'c2':[0.300534, 0.969000, 0.094000],

                   'c3':[5.689, 15.140, -0.245],

                   'GName':['KDD', 'ACC', 'QETF']})

file = pd.DataFrame({'GName':['KDD', 'ACC']})



conditions = (df['c1'] > 0.95).astype(int) + (df['c2'] > 0.5).astype(int) + (df['c3'] > 15).astype(int)

conditions = (conditions >= 2) & (df['GName'].isin(file['GName']))

df['label'] = 0

df.loc[conditions, 'label'] = 1



>>> df

         c1        c2      c3 GName  label

0  0.221445  0.300534   5.689   KDD      0

1  0.001000  0.969000  15.140   ACC      1

2  1.000000  0.094000  -0.245  QETF      0

It would be nice if you could include code to generate your dataframe in your question, as well.

answered Nov 21 at 0:12

CJ59

1,2171214

add a comment |

The way I would do it is this:

import pandas as pd



df = pd.DataFrame({'c1':[0.221445, 0.001000, 1.000000],

                   'c2':[0.300534, 0.969000, 0.094000],

                   'c3':[5.689, 15.140, -0.245],

                   'GName':['KDD', 'ACC', 'QETF']})

file = pd.DataFrame({'GName':['KDD', 'ACC']})



conditions = (df['c1'] > 0.95).astype(int) + (df['c2'] > 0.5).astype(int) + (df['c3'] > 15).astype(int)

conditions = (conditions >= 2) & (df['GName'].isin(file['GName']))

df['label'] = 0

df.loc[conditions, 'label'] = 1



>>> df

         c1        c2      c3 GName  label

0  0.221445  0.300534   5.689   KDD      0

1  0.001000  0.969000  15.140   ACC      1

2  1.000000  0.094000  -0.245  QETF      0

It would be nice if you could include code to generate your dataframe in your question, as well.

answered Nov 21 at 0:12

CJ59

1,2171214

add a comment |

The way I would do it is this:

import pandas as pd



df = pd.DataFrame({'c1':[0.221445, 0.001000, 1.000000],

                   'c2':[0.300534, 0.969000, 0.094000],

                   'c3':[5.689, 15.140, -0.245],

                   'GName':['KDD', 'ACC', 'QETF']})

file = pd.DataFrame({'GName':['KDD', 'ACC']})



conditions = (df['c1'] > 0.95).astype(int) + (df['c2'] > 0.5).astype(int) + (df['c3'] > 15).astype(int)

conditions = (conditions >= 2) & (df['GName'].isin(file['GName']))

df['label'] = 0

df.loc[conditions, 'label'] = 1



>>> df

         c1        c2      c3 GName  label

0  0.221445  0.300534   5.689   KDD      0

1  0.001000  0.969000  15.140   ACC      1

2  1.000000  0.094000  -0.245  QETF      0

It would be nice if you could include code to generate your dataframe in your question, as well.

answered Nov 21 at 0:12

CJ59

1,2171214

The way I would do it is this:

import pandas as pd



df = pd.DataFrame({'c1':[0.221445, 0.001000, 1.000000],

                   'c2':[0.300534, 0.969000, 0.094000],

                   'c3':[5.689, 15.140, -0.245],

                   'GName':['KDD', 'ACC', 'QETF']})

file = pd.DataFrame({'GName':['KDD', 'ACC']})



conditions = (df['c1'] > 0.95).astype(int) + (df['c2'] > 0.5).astype(int) + (df['c3'] > 15).astype(int)

conditions = (conditions >= 2) & (df['GName'].isin(file['GName']))

df['label'] = 0

df.loc[conditions, 'label'] = 1



>>> df

         c1        c2      c3 GName  label

0  0.221445  0.300534   5.689   KDD      0

1  0.001000  0.969000  15.140   ACC      1

2  1.000000  0.094000  -0.245  QETF      0

It would be nice if you could include code to generate your dataframe in your question, as well.

answered Nov 21 at 0:12

CJ59

1,2171214

answered Nov 21 at 0:12

CJ59

1,2171214

answered Nov 21 at 0:12

CJ59

1,2171214

answered Nov 21 at 0:12

CJ59

1,2171214

add a comment |

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