固定の文字列を検索する際に、大文字小文字の表記ゆれがあると困る場合があります。
大文字を小文字に変換、またはその逆の操作をやってみます。

元データ:data1

In [8]: data1.head()
Out[8]:
   age  workclass  fnlwgt     education  educational-num      marital-status  \
0   25    Private  226802          11th                7       Never-married
1   38    Private   89814       HS-grad                9  Married-civ-spouse
2   28  Local-gov  336951    Assoc-acdm               12  Married-civ-spouse
3   44    Private  160323  Some-college               10  Married-civ-spouse
4   18          ?  103497  Some-college               10       Never-married

          occupation relationship   race  gender  capital-gain  capital-loss  \
0  Machine-op-inspct    Own-child  Black    Male             0             0
1    Farming-fishing      Husband  White    Male             0             0
2    Protective-serv      Husband  White    Male             0             0
3  Machine-op-inspct      Husband  Black    Male          7688             0
4                  ?    Own-child  White  Female             0             0

   hours-per-week native-country income
0              40  United-States  <=50K
1              50  United-States  <=50K 2 40 United-States >50K
3              40  United-States   >50K
4              30  United-States  <=50K

任意の列のデータを変換

.str.lower()で小文字変換ができます。

例1

#  'marital-status'列をすべて小文字に変更する
data1['marital-status'] = data1['marital-status'].str.lower()
data1.head()

例1の結果

   age  workclass  fnlwgt     education  educational-num      marital-status  \
0   25    Private  226802          11th                7       never-married
1   38    Private   89814       HS-grad                9  married-civ-spouse
2   28  Local-gov  336951    Assoc-acdm               12  married-civ-spouse
3   44    Private  160323  Some-college               10  married-civ-spouse
4   18          ?  103497  Some-college               10       never-married

          occupation relationship   race  gender  capital-gain  capital-loss  \
0  Machine-op-inspct    Own-child  Black    Male             0             0
1    Farming-fishing      Husband  White    Male             0             0
2    Protective-serv      Husband  White    Male             0             0
3  Machine-op-inspct      Husband  Black    Male          7688             0
4                  ?    Own-child  White  Female             0             0

   hours-per-week native-country income
0              40  United-States  <=50K
1              50  United-States  <=50K 2 40 United-States >50K
3              40  United-States   >50K
4              30  United-States  <=50K

列名を変換

.str.upper()で大文字変換ができます。

例2

# 列名をすべて大文字に変換する
data1.columns = data1.columns.str.upper()
data1.head()

例2の結果

   AGE  WORKCLASS  FNLWGT     EDUCATION  EDUCATIONAL-NUM      MARITAL-STATUS  \
0   25    Private  226802          11th                7       never-married
1   38    Private   89814       HS-grad                9  married-civ-spouse
2   28  Local-gov  336951    Assoc-acdm               12  married-civ-spouse
3   44    Private  160323  Some-college               10  married-civ-spouse
4   18          ?  103497  Some-college               10       never-married

          OCCUPATION RELATIONSHIP   RACE  GENDER  CAPITAL-GAIN  CAPITAL-LOSS  \
0  Machine-op-inspct    Own-child  Black    Male             0             0
1    Farming-fishing      Husband  White    Male             0             0
2    Protective-serv      Husband  White    Male             0             0
3  Machine-op-inspct      Husband  Black    Male          7688             0
4                  ?    Own-child  White  Female             0             0

   HOURS-PER-WEEK NATIVE-COUNTRY INCOME
0              40  United-States  <=50K
1              50  United-States  <=50K 2 40 United-States >50K
3              40  United-States   >50K
4              30  United-States  <=50K