CODEWITHSUNDEEP
pythonnumpypandas
user1760634
user1760634

Reputation: 57

Setting values when iterating through a DataFrame

I have a dictionary of states (example IA:Idaho). I have loaded the dictionary into a DataFrame bystate_df.

then I am importing a CSV with states deaths that I want to add them to the bystate_df as I read the lines:

byState_df = pd.DataFrame(states.items())
byState_df['Deaths'] = 0
df['Deaths'] = df['Deaths'].convert_objects(convert_numeric=True)
print byState_df
for index, row in df.iterrows():
    if row['Area'] in states:
           byState_df[(byState_df[0] == row['Area'])]['Deaths'] = row['Deaths']         

print byState_df

but the byState_df is still 0 afterwords:

      0                         1  Deaths
 0   WA                Washington       0
 1   WI                 Wisconsin       0
 2   WV             West Virginia       0
 3   FL                   Florida       0
 4   WY                   Wyoming       0
 5   NH             New Hampshire       0
 6   NJ                New Jersey       0
 7   NM                New Mexico       0
 8   NA                  National       0

I test row['Deaths'] while it iterates and it's producing the correct values, it just seem to be setting the byState_df value incorrectly.

Upvotes: 1

Views: 47

Answers (1)

Jianxun Li
Jianxun Li

Reputation: 24742

Can you try the following code where I use .loc instead of [][].

byState_df = pd.DataFrame(states.items())
byState_df['Deaths'] = 0
df['Deaths'] = df['Deaths'].convert_objects(convert_numeric=True)
print byState_df
for index, row in df.iterrows():
    if row['Area'] in states:
           byState_df.loc[byState_df[0] == row['Area'], 'Deaths'] = row['Deaths']         

print byState_df

Upvotes: 1

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