qq_40820196的博客

How to select specific columnsWhen dataframe comes with a variety of types, sk.select_dtypes() will be helpful.train.select_dtypes(np.int64)for i, col in enumerate(train.select_dtypes('float')...

Difference between sns and matplotlib.pyplotsns.countplot(df_train.Census_OSInstallLanguageIdentifier, ax=axis1)df_train['Census_OSInstallLanguageIdentifier'].value_counts().plot(kind='bar')

<class 'pandas.core.frame.DataFrame'>RangeIndex: 5 entries, 0 to 4Data columns (total 11 columns):Season_Year 5 non-null int64GameKey 5 non-null int64PlayID 5 non-null int...

float_cols = df_temp.select_dtypes(include=['float'])int_cols = df_temp.select_dtypes(include=['int'])

simple way :print(train['id'].sample(1))

One-hot encoding is not required for tree-models like RF and boostings. Here I would say categorical variable do not benefit boostings but opposite.The main idea is decision-tree based models have wa...

best way to put:order = ['date', 'time', 'open', 'high', 'low', 'close', 'volumefrom', 'volumeto']df = df[order]

It’s easy to select a part of dataframe by one condition like below.pos = df_train[df_train['Date']>0]But when you are trying to add conditions like thispos = df_train[df_train['Date']>0 and...

Merge different dataframesIt’s a really confusing problem when there are a few different dataframes with correlation provided in one dataset. Now I know how to merge it together.train = train.set_in...

GroupbyIt occurs so many times that I have to record it down.dataframe before:date date_block_num shop_id item_id item_price item_cnt_day0 2013-01-02 0 59 22154 999.00 1.01 2013-01-03 0 25 2552 8...

Datedelta to intThis is the only way work for me.Y = (Y / np.timedelta64(1, 'D')).astype(int)[1]: https://blog.youkuaiyun.com/xu200yang/article/details/70460592

How to see missing data percentageSee it in textpercent = (100 * train_df.isnull().sum() / train_df.shape[0]).sort_values(ascending=False)percent[:10]trafficSource.adContent ...

Scaling have different affection on regression or decisiontreeScaling is a necessary step of preprocessing,it can help eliminating the bias caused by variable with different scales. It works in SVM o...

sklearn.preprocessing.LabelEncoder() & pandas.factorizeI am used to usedata.loc[:, "MSZoning"] = pd.factorize(data.MSZoning)[0]Actually what it does is exactly the same with LabelEncoder. The ...

How to check NaN in df swiftly?To check NaN in a dataframe.train.isnull().sum()Id 0v2a1 6860hacdor 0rooms 0hacapo ...

copy() & deepcopy()When we copy one column in a dataframe to use,we are usually talking about .deepcopy() – to take the copy as another new one. As for .copy(), it remains synchronization with...

2 way to transform from different type: .loc or mappingWhen we have to tranform a column from type to type,here are two ways: 1all_data.loc[all_data["edjefe"]=="yes","edjefe&quot

def rmse(y, y_pred): return np.sqrt(mean_squared_error(y, y_pred))