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<p>我试图从数据框中的下一列创建两个单独的列</p>
<pre><code>0 State_1
1 Auburn
2 Florence
3 Jacksonville
4 Livingston
5 Montevallo
6 Troy
7 Tuscaloosa
8 Tuskegee
9 state_2
10 Fairbanks
11 state_3
12 Flagstaff
13 Tempe
14 Tucson
15 state_4
16 Arkadelphia
17 Conway
18 Fayetteville
19 Jonesboro
20 Magnolia
21 Monticello
22 Russellville
23 Searcy
</code></pre>
<p>我希望上面的df看起来像这样:</p>
<pre><code>0 state_1 Auburn
2 state_1 Florence
3 state_1 Jacksonville
4 state_1 Livingston
5 state_1 Montevallo
6 state_1 Troy
7 state_1 Tuscaloosa
8 state_1 Tuskegee
...
16 state_4 Arkadelphia
17 state_4 Conway
18 state_4 Fayetteville
19 state_4 Jonesboro
20 state_4 Magnolia
21 state_4 Monticello
22 state_4 Russellville
23 v Searcy
</code></pre>
<p>如您所见,我想对数据进行反向透视。我查阅了pd.pivot上的文档,但没有取得任何进展。这是一本国家词典:</p>
<pre><code>states = {'OH': 'Ohio', 'KY': 'Kentucky', 'AS': 'American Samoa', 'NV': 'Nevada', 'WY': 'Wyoming', 'NA': 'National', 'AL': 'Alabama', 'MD': 'Maryland', 'AK': 'Alaska', 'UT': 'Utah', 'OR': 'Oregon', 'MT': 'Montana', 'IL': 'Illinois', 'TN': 'Tennessee', 'DC': 'District of Columbia', 'VT': 'Vermont', 'ID': 'Idaho', 'AR': 'Arkansas', 'ME': 'Maine', 'WA': 'Washington', 'HI': 'Hawaii', 'WI': 'Wisconsin', 'MI': 'Michigan', 'IN': 'Indiana', 'NJ': 'New Jersey', 'AZ': 'Arizona', 'GU': 'Guam', 'MS': 'Mississippi', 'PR': 'Puerto Rico', 'NC': 'North Carolina', 'TX': 'Texas', 'SD': 'South Dakota', 'MP': 'Northern Mariana Islands', 'IA': 'Iowa', 'MO': 'Missouri', 'CT': 'Connecticut', 'WV': 'West Virginia', 'SC': 'South Carolina', 'LA': 'Louisiana', 'KS': 'Kansas', 'NY': 'New York', 'NE': 'Nebraska', 'OK': 'Oklahoma', 'FL': 'Florida', 'CA': 'California', 'CO': 'Colorado', 'PA': 'Pennsylvania', 'DE': 'Delaware', 'NM': 'New Mexico', 'RI': 'Rhode Island', 'MN': 'Minnesota', 'VI': 'Virgin Islands', 'NH': 'New Hampshire', 'MA': 'Massachusetts', 'GA': 'Georgia', 'ND': 'North Dakota', 'VA': 'Virginia'}
</code></pre>
<p>这是我试过的代码。请注意,这是一个令人尴尬的错误尝试(这里几乎是Python新手)</p>
<pre><code>#create new column for states only
df['State'] = 0
#Duplicate above combined column
df['Column_duplicate'] = df['Column']
for i in range(len(df)):
if (dfl['Column_duplicate'].iloc[i+1] == df['Column'].iloc[i]):
dfl['State'].iloc[i] = dfl['Column'].iloc[i]
</code></pre>