Get Column Index from Label in a Data Frame

Get column index from column name in python pandas

Sure, you can use .get_loc():

In [45]: df = DataFrame({"pear": [1,2,3], "apple": [2,3,4], "orange": [3,4,5]})

In [46]: df.columns
Out[46]: Index([apple, orange, pear], dtype=object)

In [47]: df.columns.get_loc("pear")
Out[47]: 2

although to be honest I don't often need this myself. Usually access by name does what I want it to (df["pear"], df[["apple", "orange"]], or maybe df.columns.isin(["orange", "pear"])), although I can definitely see cases where you'd want the index number.

Get column index from label in a data frame

you can get the index via grep and colnames:

grep("B", colnames(df))
[1] 2

or use

grep("^B$", colnames(df))
[1] 2

to only get the columns called "B" without those who contain a B e.g. "ABC".

Retrieve name of column from its Index in Pandas

I think you need index columns names by position (python counts from 0, so for fourth column need 3):

colname = df.columns[pos]

Sample:

df = pd.DataFrame({'A':[1,2,3],
                   'B':[4,5,6],
                   'C':[7,8,9],
                   'D':[1,3,5],
                   'E':[5,3,6],
                   'F':[7,4,3]})

print (df)
   A  B  C  D  E  F
0  1  4  7  1  5  7
1  2  5  8  3  3  4
2  3  6  9  5  6  3

pos = 3
colname = df.columns[pos]
print (colname)
D

---

pos = [3,5]
colname = df.columns[pos]
print (colname)
Index(['D', 'F'], dtype='object')

Get column index label based on values

I will save the result in a list because otherwise there could be more than one column with values ​​equal to 1. You can use DataFrame.loc

if all column values ​​must be 1 then you can use:

df.loc[:,df.eq(1).all()].columns.tolist()

Output:

['C3']

---

if this isn't necessary then use:

df.loc[:,df.eq(1).any()].columns.tolist()

or as suggested @piRSquared, you can select directly from df.columns:

[*df.columns[df.eq(1).all()]]

get column number from label in DataFrame

You need Index.get_loc or Index.searchsorted:

a = df.columns.get_loc('key')
print (a)
1

---

a = df.columns.searchsorted('key')
print (a)
1

Then iloc works nice:

a = df.iloc[2, df.columns.get_loc('key')]
print (a)
a

Pandas: Get column index/label of a specific single value in a row from among multiple columns of mutually exclusive choice

You can check for the column values equal 1 across the row and get the column index corresponding to True (for entries of 1) by .idxmax() (with axis=1 for getting column index), as follows:

df['age_group'] = df.eq(1).idxmax(axis=1)

Result:

print(df)

   21_30  31_40  40_49  50_59 age_group
0      0      0      0      1     50_59
1      0      1      0      0     31_40
2      0      1      0      0     31_40
3      1      0      0      0     21_30
4      0      0      1      0     40_49

Pandas index column title or name

You can just get/set the index via its name property

In [7]: df.index.name
Out[7]: 'Index Title'

In [8]: df.index.name = 'foo'

In [9]: df.index.name
Out[9]: 'foo'

In [10]: df
Out[10]: 
         Column 1
foo              
Apples          1
Oranges         2
Puppies         3
Ducks           4

Get column names with corresponding index in python pandas

Simpliest is add pd.Series constructor:

pd.Series(list(df.columns))

Or convert columns to Series and create default index:

df.columns.to_series().reset_index(drop=True)

Or:

df.columns.to_series(index=False)

Efficient way to get indices of column-labels from pd.DataFrame

short_way = [df.columns.get_loc(col) for col in query_cols]
print(sorted(short_way))
# outputs [0, 2, 5, 6]

Pandas: Get cell value by row index and column name

Use .loc to get rows by label and .iloc to get rows by position:

>>> df.loc[3, 'age']
23

>>> df.iloc[2, df.columns.get_loc('age')]
23

More about Indexing and selecting data

---

Related Topics